Projection screen control method and projection device

Abstract

The application relates to a projection picture control method and a projection device. The method comprises the following steps: sequentially acquiring a plurality of groups of current scene data and initial scene data of a preset identification area; performing numerical comparison processing on the initial scene data and the plurality of groups of current scene data to obtain a comparison result; regarding a detection point corresponding to a case that the comparison result satisfies a first preset condition as a current depth detection point; when the number of the current depth detection points in the current scene data exceeds a first preset threshold, performing shape identification on the current depth detection points in the group of current scene data, and regarding a shape satisfying a second preset condition as an effective detection shape; obtaining a current motion track according to current depth detection points in current scene data corresponding to the plurality of groups of effective detection shapes; and generating a picture operation instruction according to the current motion track, so that convenient control of a projection picture is realized, a special interactive device is not needed, the cost is low, the control of the picture is not limited by the size of the projection picture, and the user can conveniently control the picture.

Description

Technical Field

[0001] This application relates to the field of projection processing technology, and in particular to a projection screen control method and projection device. Background Technology

[0002] A projector, also known as a projector, is a device that projects images or videos onto a screen or wall. Currently, projector screen interaction can be divided into indirect and direct control. Indirect control is generally achieved through interactive devices such as remote controls, mice, and keyboards. However, indirect control requires users to utilize these devices, resulting in high hardware costs, fixed operation methods, and a less than ideal user experience. Direct control typically requires users to touch the projector screen. When a user wants to operate a function on the projected screen, they need to reach their hand to the corresponding function. However, projectors usually project large images, such as 100 inches, 120 inches, or 200 inches, making it inconvenient for users.

[0003] During the implementation process, the inventors discovered that traditional technologies have at least the following problems: existing projection screen control methods are costly, have poor interactive convenience, and offer a poor interactive experience. Summary of the Invention

[0004] Therefore, it is necessary to address the problems existing in the above-mentioned existing projection screen control methods by providing a projection screen control method and projection device that can improve the convenience of projection screen interaction, requires no special interaction device, is low in cost, is not limited by the size of the projection screen, and facilitates user operation of the screen.

[0005] In a first aspect, this application provides a method for controlling a projected image, comprising the following steps:

[0006] The system acquires multiple sets of current scene data for a preset recognition area in a time sequence, as well as initial scene data for the preset recognition area. The initial scene data includes initial depth information of multiple detection points, and the current scene data includes current depth information of multiple detection points.

[0007] The initial scene data is numerically compared with multiple sets of current scene data to obtain the comparison result; and the detection point corresponding to the comparison result that meets the first preset condition is taken as the current depth detection point.

[0008] When the number of current depth detection points in the current scene data exceeds the first preset threshold, shape recognition is performed on the current depth detection points in the current scene data, and the shapes that meet the second preset conditions are confirmed as valid detection shapes.

[0009] The current motion trajectory is obtained based on the current depth detection point in the current scene data corresponding to multiple sets of effective detection shapes;

[0010] Generate screen operation instructions based on the current motion trajectory.

[0011] Optionally, before the steps of acquiring multiple sets of current scene data for the preset recognition area in a time sequence and acquiring the initial scene data for the preset recognition area, the following steps are included:

[0012] Obtain the detection area and the initial projection area located within the detection area;

[0013] Based on the detection area and the initial projection area, the recognition area is selected to obtain the preset recognition area; the preset recognition area is located below the initial projection area and / or below the detection area.

[0014] Optionally, before acquiring multiple sets of current scene data for the preset recognition area in a time sequence and acquiring the initial scene data for the preset recognition area, the following steps are also included:

[0015] Acquire second current scene data within a preset recognition area; when the change between the second current scene data and the initial scene data within the preset recognition area exceeds a second preset threshold, update the second current scene data to the initial scene data; and / or

[0016] Acquire the device's motion change parameters; when the motion change parameters exceed a third preset threshold, acquire the second current scene data within the preset recognition area and update the second current scene data to the initial scene data.

[0017] Optionally, when the number of current depth detection points in the current scene data exceeds a first preset threshold, the step of performing shape recognition on the current depth detection points in the current scene data set and confirming shapes that meet the second preset condition as valid detection shapes includes:

[0018] When the number of current depth detection points in the current scene data exceeds the first preset threshold, the contour shape formed by the current depth detection points in the current scene data is identified and processed to obtain the current detection shape.

[0019] Based on a gesture recognition database, the current detected shape is matched, and if the matching result meets a second preset condition, the current detected shape is confirmed as a valid detected shape; or,

[0020] When the number of current depth detection points in the current scene data exceeds the first preset threshold, obtain the maximum horizontal dimension and the maximum vertical dimension of the contour shape formed by the current depth detection points in the current scene data.

[0021] When the ratio between the maximum horizontal dimension and the maximum vertical dimension meets the second preset condition, the current detection shape is confirmed as a valid detection shape.

[0022] Optionally, the step of obtaining the current motion trajectory based on the current depth detection point in the current scene data corresponding to multiple sets of valid detection shapes includes:

[0023] If the number of confirmed valid detection shapes meets the fourth preset threshold, and the acquisition time interval of the current scene data corresponding to the confirmed valid detection shapes is within a preset time, then the current motion trajectory is obtained based on the specific detection points in multiple sets of corresponding current scene data; the specific detection points are obtained based on the current detection points.

[0024] Optionally, if the number of confirmed valid detection shapes meets a fourth preset threshold, and the acquisition time interval of the current scene data corresponding to the confirmed valid detection shapes is within a preset time, then the step of obtaining the current motion trajectory based on specific detection points in multiple sets of corresponding current scene data includes:

[0025] Acquire the detection point data set corresponding to the valid detection shape, and transmit the detection point data set to the first queue in sequence; the detection point data set includes the spatial data of each current depth detection point corresponding to the valid detection shape.

[0026] If the number of probe point data groups in the first queue meets the fourth preset threshold, and the interval input time between the first and last probe point data groups reaches the preset time when the fourth preset threshold is met, then the current motion trajectory is obtained based on the spatial data of specific probe points in each probe point data group.

[0027] Optionally, after the step of acquiring the detection point data set corresponding to the valid detection shape and sequentially transmitting the detection point data set to the first queue, the following steps are included:

[0028] If, at each preset time interval, the number of probe point data groups in the first queue is less than the fourth preset threshold, then the probe point data groups in the first queue are cleared; or

[0029] If the interval between the first and last group of probe point data in the first queue exceeds the preset time when the fourth preset threshold is met, the probe point data in the first queue will be cleared.

[0030] Optionally, the steps for obtaining the current motion trajectory based on specific detection points in multiple sets of corresponding current scene data include:

[0031] Acquire the location information of specific detection points in multiple sets of current scene data corresponding to the effective detection shapes in a time sequence;

[0032] Based on the acquisition sequence of the current scene data of each corresponding effective detection shape, if the coordinate values ​​of each specific detection point position information in the first spatial direction increase or decrease, and the maximum coordinate change value in the position information of each specific detection point is greater than the fifth preset threshold, the current motion trajectory is determined to be a trajectory moving along the first spatial direction.

[0033] Based on the acquisition sequence of the current scene data of each corresponding effective detection shape, if the coordinate values ​​of each specific detection point position information in the second spatial direction increase or decrease, and the maximum coordinate change value in the position information of each specific detection point is greater than the sixth preset threshold, the current motion trajectory is determined to be a trajectory moving along the second spatial direction.

[0034] When the maximum coordinate change value in the position information of each specific detection point in the third spatial direction is greater than the seventh preset threshold, the current motion trajectory is determined to be a trajectory moving along the third spatial direction.

[0035] Optionally, the step of acquiring the location information of specific detection points in multiple sets of current scene data corresponding to the effective detection shape in a time sequence includes:

[0036] The spatial coordinates of the current depth detection point in multiple sets of current scene data corresponding to the effective detection shape are obtained sequentially.

[0037] The spatial coordinates of each set of current depth detection points are averaged to obtain the specific detection point location information corresponding to the effective detection shape; or,

[0038] The spatial coordinates of the current depth detection point in multiple sets of current scene data corresponding to the effective detection shape are obtained sequentially.

[0039] The coordinates of the current depth detection point with the largest or smallest coordinate value in the first direction are used as the specific detection point location information for that set of effective detection shapes.

[0040] Optionally, the number of preset recognition regions is at least two; the preset recognition regions are located within the overlapping area formed by the left 1 / 3 and the lower 1 / 2 regions of the initial projection region, and / or within the overlapping area formed by the right 1 / 3 and the lower 1 / 2 regions of the initial projection region; the step of obtaining the initial scene data of the preset recognition regions includes:

[0041] Acquire human feature location data within the detection area;

[0042] The human body feature location data is compared with each preset recognition area, and based on the comparison results, the initial scene data of the preset recognition area close to the human body feature location data is obtained.

[0043] Optionally, the step of acquiring multiple sets of current scene data for a preset recognition area in a time sequence includes the following:

[0044] It receives screen operation requests and generates gesture operation indicator boxes in the projection screen area corresponding to the preset recognition area according to the screen operation requests.

[0045] Secondly, this application provides a projection device, including a detection module and a processor, wherein the detection module is connected to the processor; the processor is used to execute the steps of any of the above-described control methods for projecting images.

[0046] One of the above technical solutions has the following advantages and beneficial effects:

[0047] In the above-described method for controlling the projected image, multiple sets of current scene data and initial scene data of the preset recognition area are acquired sequentially. The initial scene data includes initial depth information of multiple detection points, and the current scene data includes current depth information of multiple detection points. The initial scene data and multiple sets of current scene data are numerically compared to obtain a comparison result. The detection point corresponding to the comparison result satisfying the first preset condition is taken as the current depth detection point. When the number of current depth detection points in the current scene data exceeds the first preset threshold, shape recognition is performed on the current depth detection points in the set of current scene data, and the shape satisfying the second preset condition is confirmed as a valid detection shape. The current motion trajectory is obtained based on the current depth detection points in the current scene data corresponding to multiple sets of valid detection shapes. Based on the current motion trajectory, screen operation instructions are generated to achieve convenient control of the projected image. This application identifies valid detection shapes and their current motion trajectories within a preset recognition area, and then generates screen operation commands based on the current motion trajectory. This allows users to operate the selection boxes on the projected screen using gestures, thereby controlling the function boxes on the projected screen. This provides users with convenient interaction with the projected screen, eliminates the need for dedicated interaction devices, reduces costs, and is not limited by the size of the projected screen. It solves the problem of difficult touch operation in large-screen projection and makes it easier for users to control the screen. Attached Figure Description

[0048] Figure 1 This is a schematic diagram illustrating an application scenario of the control method for the projected image in the embodiments of this application;

[0049] Figure 2 This is a first flowchart illustrating the control method for the projected image in an embodiment of this application;

[0050] Figure 3 This is a second flowchart illustrating the control method for the projected image in an embodiment of this application;

[0051] Figure 4This is a schematic diagram of the first process of the effective shape detection processing steps in the embodiments of this application;

[0052] Figure 5 This is a schematic diagram of the second process of the effective shape detection processing step in the embodiments of this application;

[0053] Figure 6 This is a schematic diagram of the third process of the control method for the projected image in the embodiments of this application;

[0054] Figure 7 This is a schematic diagram of the first process of the current motion trajectory processing step in the embodiments of this application;

[0055] Figure 8 This is a second flowchart illustrating the current motion trajectory processing step in an embodiment of this application;

[0056] Figure 9 This is a schematic diagram of the fourth process of the control method for the projected image in the embodiments of this application;

[0057] Figure 10 This is a first schematic diagram of the preset recognition area division of the control method for the projected image in the embodiments of this application;

[0058] Figure 11 This is a schematic diagram illustrating the current depth detection point identification in the control method of the projected image in the embodiments of this application;

[0059] Figure 12 This is a schematic diagram of the shape recognition method for controlling the projected image in the embodiments of this application;

[0060] Figure 13 This is a schematic diagram of the detection point data group of the control method for the projected image in an embodiment of this application.

[0061] Figure 14 This is a schematic diagram illustrating the positional changes of specific detection point location information in the control method for projected images in this embodiment of the application.

[0062] Figure 15 This is a schematic diagram of the selection box movement in the control method of the projected screen in the embodiments of this application;

[0063] Figure 16 This is a second schematic diagram illustrating the preset recognition area division of the projection screen control method in this embodiment of the application.

[0064] Figure 17 This is a schematic diagram illustrating the selection of specific detection point location information in the control method for the projected image in this embodiment of the application.

[0065] Figure 18 This is a schematic diagram of the projection device in the embodiments of this application. Detailed Implementation

[0066] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0067] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0068] In this application, the terms "upper," "lower," "left," "right," "front," "rear," "top," "bottom," "inner," "outer," "middle," "vertical," "horizontal," "lateral," and "longitudinal" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are primarily for the purpose of better describing this application and its embodiments, and are not intended to limit the indicated device, element, or component to having a specific orientation, or to be constructed and operated in a specific orientation.

[0069] Furthermore, in addition to indicating location or positional relationship, some of the aforementioned terms may also have other meanings. For example, the term "above" may also be used in some cases to indicate a certain dependency or connection relationship. Those skilled in the art can understand the specific meaning of these terms in this application based on the specific circumstances.

[0070] In addition, the term "multiple" should mean two or more.

[0071] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0072] The projection screen control method provided in this application can be applied to, for example... Figure 1In the application environment shown, the processing device may include a processor 102 and a detection module 104. The processor 102 is connected to the detection module 104. The processor 102 can be used to acquire multiple sets of current scene data and initial scene data of a preset recognition area in a time sequence. The initial scene data includes initial depth information of multiple detection points, and the current scene data includes current depth information of multiple detection points. The initial scene data and multiple sets of current scene data are numerically compared to obtain a comparison result. The detection point corresponding to the comparison result that meets a first preset condition is taken as the current depth detection point. When the number of current depth detection points in the current scene data exceeds a first preset threshold, the current depth detection points in the set of current scene data are shape-recognized, and the shape that meets a second preset condition is confirmed as a valid detection shape. The current motion trajectory is obtained based on the current depth detection points in the current scene data corresponding to multiple sets of valid detection shapes. The screen operation command is generated based on the current motion trajectory. The detection module 104 can be used to output detection light to the detection area. The detection module 104 can also obtain the current scene data and initial scene data of the corresponding detection area based on the detection light output to the detection area. The processing device can be a projection device, the processor 102 can be the host processor 102 of the projector, and the detection module 104 can be a lidar module, for example, the detection module 104 can be an area array lidar ranging radar module.

[0073] In one embodiment, such as Figure 2 As shown, a method for controlling a projected image is provided, which can be applied to... Figure 1 Taking the processor in the example, the following steps are included:

[0074] Step S210: Acquire multiple sets of current scene data of the preset recognition area and the initial scene data of the preset recognition area in a time sequence; the initial scene data includes the initial depth information of multiple detection points, and the current scene data includes the current depth information of multiple detection points.

[0075] The preset recognition area is provided to the user for gesture control. For example, the preset recognition area is located within the detection area. The detection module can be used to project a detection array onto the detection area. The detection array includes multiple detection points. The initial scene data can be the scene data obtained when the detection module first projects the detection array onto the preset recognition area after system power-on initialization; the initial scene data may include the initial depth information of multiple detection points. The current scene data refers to the scene data obtained after the initial detection when the detection module projects the detection array onto the preset recognition area; the current scene data includes the current depth information of multiple detection points.

[0076] For example, the detection module may include millimeter-wave radar, infrared light, ultrasound, etc., and distance measurement methods include ITOF and DTOF, hereinafter referred to as TOF (Time of Flight) sensors. Taking the emission of infrared light as an example, the TOF sensor emits modulated near-infrared light, which is reflected after encountering an object. The TOF sensor calculates the distance to the object by calculating the time difference or phase difference between the emission and reflection of the light, thus generating corresponding depth information. It should be noted that the current scene data obtained by the detection module is acquired frame by frame. The detection module can acquire several to dozens of frames of data per second, and each frame includes a large amount of current depth information of the detection points.

[0077] The TOF sensor can emit a large number of detection rays within its detection range. The detection array is the collection of all detection rays projected from the TOF sensor. Each ray is a detection point, and each detection point has corresponding emission angle information. The TOF sensor can calculate the distance information of the object detected by each detection point, thus knowing the depth information of each reflected detection point. The depth information of each detection point is then transmitted to the processor, which in turn obtains the current scene data of the preset recognition area and the initial scene data of the preset recognition area.

[0078] The detection module can emit a large number of detection rays to the preset recognition area based on a preset cycle, and obtain the current scene data based on the emitted detection rays. The current scene data is then transmitted to the processor, and the processor can obtain multiple sets of current scene data of the preset recognition area in a time sequence.

[0079] Step S220: Perform numerical comparison processing on the initial scene data and multiple sets of current scene data to obtain the comparison result; and take the detection point corresponding to the comparison result that meets the first preset condition as the current depth detection point.

[0080] The processor can process the initial scene data to obtain initial depth information for multiple detection points; the processor can also process the current scene data to obtain current depth information for multiple detection points. The processor can perform numerical comparison processing between the initial scene data and multiple sets of current scene data, that is, compare the initial depth information of each detection point with the corresponding set of current depth information to obtain a depth information comparison value. The detection point corresponding to the depth information comparison data that satisfies a first preset condition can then be used as the current depth detection point.

[0081] For example, the processor can perform difference processing on the initial depth information of each probe and the current depth information of the corresponding group to obtain the depth change value of each probe point relative to the initial scene data. Further, the depth change data of the corresponding group is compared with a preset threshold, and the probe point corresponding to the depth change data of the corresponding group being greater than or equal to the preset threshold is taken as the current depth probe point of the corresponding group.

[0082] Step S230: When the number of current depth detection points in the current scene data exceeds the first preset threshold, perform shape recognition on the current depth detection points in the current scene data and confirm the shapes that meet the second preset conditions as valid detection shapes.

[0083] The processor counts the number of current depth detection points in the corresponding group. When the number of current depth detection points in the current scene data exceeds the first preset threshold, the processor performs shape recognition on the current depth detection points in the current scene data of that group to determine whether the shape they form conforms to a preset shape (such as an arm shape). Then, the shape that meets the second preset condition is confirmed as a valid detection shape.

[0084] It should be noted that if the number of current depth detection points in the current scene data does not exceed the first preset threshold, the current scene data of the corresponding group will be considered invalid data.

[0085] Step S240: Obtain the current motion trajectory based on the current depth detection point in the current scene data corresponding to multiple sets of valid detection shapes.

[0086] For example, the processor can identify the position change of the current depth detection points in the current scene data corresponding to multiple effective detection shapes, that is, identify the position change amount and position change direction of the corresponding current depth detection points in each group, and then obtain the current motion trajectory based on the position change amount and position change direction.

[0087] Step S250: Generate screen operation instructions based on the current motion trajectory.

[0088] Among them, the screen operation commands can be used to instruct the projector's operating system to perform the corresponding selection box operations.

[0089] For example, the current motion trajectory can be established based on a three-dimensional spatial coordinate system. For instance, a three-dimensional spatial coordinate system includes an X-axis, a Y-axis, and a Z-axis, where the X, Y, and Z axes each have positive and negative directions. If the current motion trajectory indicates movement in the negative X-axis direction, the processor, based on the current motion trajectory, transmits the generated screen operation command corresponding to the negative X-axis movement to the projector's operating system. The projector's operating system then controls the selection box to move in the negative X-axis direction (i.e., moves the selection box to the left). If the current motion trajectory indicates movement in the positive X-axis direction, the processor, based on the current motion trajectory, transmits the generated screen operation command corresponding to the positive X-axis movement to the projector's operating system. The projector's operating system then controls the selection box to move in the positive X-axis direction (i.e., moves the selection box to the right). If the current motion trajectory indicates movement in the negative Y-axis direction, the processor, based on the current motion trajectory, transmits the generated screen operation command corresponding to the positive X-axis movement to the projector's operating system. The projector's operating system then controls the selection box to move in the positive X-axis direction (i.e., moves the selection box to the right). The generated screen operation command corresponding to the negative Y-axis movement is transmitted to the projector's operating system, which then controls the selection box to move in the negative Y-axis direction (i.e., moves the selection box down). If the current motion trajectory indicates movement in the positive Y-axis direction, the processor, based on the current motion trajectory, transmits the generated screen operation command corresponding to the positive Y-axis movement to the projector's operating system, which then controls the selection box to move in the positive Y-axis direction (i.e., moves the selection box up). If the current motion trajectory indicates movement in either the negative or positive Z-axis direction, the processor, based on the current motion trajectory, transmits the generated screen operation command corresponding to the negative or positive Z-axis movement to the projector's operating system, which then performs a click / confirm operation on the selection box (i.e., clicks or confirms the selection box).

[0090] In the above embodiments, multiple sets of current scene data and initial scene data of the preset recognition area are acquired sequentially. The initial scene data includes initial depth information of multiple detection points, and the current scene data includes current depth information of multiple detection points. The initial scene data and multiple sets of current scene data are numerically compared to obtain a comparison result. The detection point corresponding to the comparison result satisfying the first preset condition is taken as the current depth detection point. When the number of current depth detection points in the current scene data exceeds the first preset threshold, shape recognition is performed on the current depth detection points in the set of current scene data, and the shape that satisfies the second preset condition is confirmed as a valid detection shape. The current motion trajectory is obtained based on the current depth detection points in the current scene data corresponding to multiple sets of valid detection shapes. Based on the current motion trajectory, screen operation instructions are generated to achieve convenient control of the projected screen. This application identifies valid detection shapes and their current motion trajectories within a preset recognition area, and then generates screen operation commands based on the current motion trajectory. This allows users to operate the selection boxes on the projected screen using gestures, thereby controlling the function boxes on the projected screen. This provides users with convenient interaction with the projected screen, eliminates the need for dedicated interaction devices, reduces costs, and is not limited by the size of the projected screen. It solves the problem of difficult touch operation in large-screen projection and makes it easier for users to control the screen.

[0091] In one embodiment, such as Figure 3 As shown, a method for controlling a projected image is provided, which can be applied to... Figure 1 Taking the processor in the example, the explanation includes the following steps:

[0092] Step S310: Obtain the detection area and the initial projection area located within the detection area.

[0093] The detection area is greater than or equal to the initial projection area, and the initial projection area is located within the detection area. The detection area refers to the region where the detection module emits its detection array, and the initial projection area refers to the region of the projected image.

[0094] Step S320: Select the recognition area based on the detection area and the initial projection area to obtain a preset recognition area; the preset recognition area is located below the initial projection area and / or below the detection area.

[0095] The processor selects a recognition region based on the acquired detection region and initial projection region, thereby obtaining a preset recognition region. The preset recognition region can be located in the lower region of the initial projection region, or it can be located in the lower region of the detection region. Furthermore, the preset recognition region can also be located in both the lower regions of the initial projection region and the lower regions of the detection region. It should be noted that the lower region within the initial projection region can be a local area below the horizontal center line of the initial projection region; the lower region within the detection region can also be a local area below the horizontal center line of the detection region. Further, the lower region within the initial projection region can be a local area below the horizontal center line of the initial projection region and close to the region boundary line; the lower region within the detection region can also be a local area below the horizontal center line of the detection region and close to the region boundary line.

[0096] For example, such as Figure 10 As shown, the preset recognition area can be selected as the lower left and / or lower right area within the initial projection area. Preferably, the preset recognition area is within the left 1 / 3 and lower 1 / 2 areas of the initial projection area, or within the overlapping area formed by the right 1 / 3 and lower 1 / 2 areas. It should be noted that the lower 1 / 2 area refers to the lower half of the initial projection area, and the right 1 / 3 area is the rightmost area in the horizontally divided 3-part region of the initial projection area, and so on. Further, the preset recognition area can be narrowed to the overlapping area formed by the left 1 / 4 and lower 1 / 3 areas, or the overlapping area formed by the right 1 / 4 and lower 1 / 3 areas. This preset recognition area is positioned so that users can interact with the projected image by simply placing their hand outside the projection screen and making gestures at the bottom edge of the image. This facilitates user operation. Additionally, the preset recognition area significantly reduces the data volume compared to the entire detection range, thus accelerating the comparison and calculation efficiency of subsequent processes.

[0097] For example, the preset identification area can also be set in the lower left or lower right region of the detection area. For instance, the preset identification area is preferably within the overlapping area formed by the left 1 / 3 and lower 1 / 2 regions of the detection area, or the right 1 / 3 and lower 1 / 2 regions. Further, the preset identification area can be narrowed to the overlapping area formed by the left 1 / 4 and lower 1 / 3 regions of the detection area, or the right 1 / 4 and lower 1 / 3 regions.

[0098] It should be noted that the position of the preset recognition area in the detection area can be pre-set, or it can be customized or selected by the user in a specific function interface.

[0099] Step S330: Acquire multiple sets of current scene data of the preset recognition area and the initial scene data of the preset recognition area in a time sequence; the initial scene data includes the initial depth information of multiple detection points, and the current scene data includes the current depth information of multiple detection points.

[0100] For a detailed explanation of step S330 above, please refer to the description of the above embodiments, which will not be repeated here.

[0101] Step S340: Perform numerical comparison processing on the initial scene data and multiple sets of current scene data to obtain the comparison result; and take the detection point corresponding to the comparison result that meets the first preset condition as the current depth detection point.

[0102] For a detailed explanation of step S340 above, please refer to the description of the above embodiments, which will not be repeated here.

[0103] Step S350: When the number of current depth detection points in the current scene data exceeds the first preset threshold, perform shape recognition on the current depth detection points in the current scene data and confirm the shapes that meet the second preset conditions as valid detection shapes.

[0104] For a detailed explanation of step S350, please refer to the description of the above embodiments, which will not be repeated here.

[0105] Step S360: Obtain the current motion trajectory based on the current depth detection point in the current scene data corresponding to multiple sets of valid detection shapes.

[0106] For a detailed explanation of step S360, please refer to the description of the above embodiments, which will not be repeated here.

[0107] Step S370: Generate screen operation instructions based on the current motion trajectory.

[0108] For a detailed explanation of step S370, please refer to the description of the above embodiments, which will not be repeated here.

[0109] In the above embodiments, by selecting a preset recognition area, valid detection shapes and their current motion trajectories are identified within the preset recognition area. Then, based on the current motion trajectory, screen operation instructions are generated, allowing users to operate the selection box on the projected screen based on gestures, thereby controlling the function boxes on the projected screen. This provides users with convenient interaction with the projected screen, eliminates the need for dedicated interaction devices, reduces costs, and is not limited by the size of the projected screen. It solves the problem of difficult touch operation in large-screen projection and makes it more convenient for users to control the screen.

[0110] In one embodiment, before acquiring multiple sets of current scene data for a preset recognition region in a time sequence and acquiring the initial scene data for the preset recognition region, the method further includes the following steps:

[0111] Acquire second current scene data within a preset recognition area; when the change between the second current scene data and the initial scene data within the preset recognition area is greater than a second preset threshold, update the second current scene data to the initial scene data; and / or acquire the device's action change parameters; when the action change parameters are greater than a third preset threshold, acquire the second current scene data within the preset recognition area and update the second current scene data to the initial scene data.

[0112] The second current scene data can be the scene data of the preset recognition area obtained by the detection module when the projector enters the initial scene calibration mode. It should be noted that in the initial scene calibration mode, there are no obstacles (such as the user's arm) obstructing the preset recognition area.

[0113] The processor can proactively acquire second current scene data within a preset recognition area based on a preset period, or acquire second current scene data within a preset recognition area based on user instructions. Based on the acquired second current scene data, the processor enters an initial scene calibration mode, performs numerical comparison processing between the second current scene data and the initial scene data within the preset recognition area. When the change in the comparison between the second current scene data and the initial scene data within the preset recognition area exceeds a second preset threshold, it is determined that the depth information of the initial scene has changed, and the second current scene data is then updated to the initial scene data.

[0114] For example, the motion change parameters of the device can be detected by the motion sensor set in the projector itself. The processor can acquire the motion change parameters of the device and compare the value of the motion change parameters with a third preset threshold. When the motion change parameters are greater than the third preset threshold, it is determined that the depth information of the initial scene has changed. Then, the processor acquires the second current scene data within the preset recognition area and updates the initial scene data with the second current scene data. This enables timely updates to the initial scene data when a change in the position of the initial scene is detected, avoiding data errors in subsequent steps and improving the accuracy of the projected image control.

[0115] In one embodiment, such as Figure 4 As shown, when the number of current depth detection points in the current scene data exceeds a first preset threshold, the step of performing shape recognition on the current depth detection points in the current scene data and confirming shapes that meet the second preset condition as valid detection shapes includes:

[0116] Step S410: When the number of current depth detection points in the current scene data exceeds the first preset threshold, the contour shape formed by the current depth detection points in the current scene data is identified and processed to obtain the current detection shape.

[0117] The processor determines the number of current depth detection points in the current scene data of the corresponding group. When the number of current depth detection points in the current scene data of the corresponding group exceeds the first preset threshold, the processor identifies the contour shape formed by the current depth detection points in the current scene data of the group to obtain the current detection shape.

[0118] Step S420: Based on the gesture recognition database, perform matching processing on the current detection shape, and when the matching result meets the second preset condition, confirm the current detection shape as a valid detection shape.

[0119] The gesture recognition database can be pre-stored in the projector's memory. Based on the gesture recognition database, the processor performs matching processing on the current detected shape, determines whether the current detected shape conforms to a preset shape (such as an arm shape), and confirms the current detected shape as a valid detected shape when the matching result meets a second preset condition, thereby realizing the shape recognition of objects within the preset recognition area.

[0120] In one embodiment, such as Figure 5 As shown, when the number of current depth detection points in the current scene data exceeds a first preset threshold, the step of performing shape recognition on the current depth detection points in the current scene data and confirming shapes that meet the second preset condition as valid detection shapes includes:

[0121] Step S510: When the number of current depth detection points in the current scene data exceeds the first preset threshold, obtain the maximum horizontal dimension and the maximum vertical dimension of the contour shape formed by the current depth detection points in the current scene data.

[0122] The processor determines the number of current depth detection points in the current scene data of the corresponding group. When the number of current depth detection points in the current scene data of the corresponding group exceeds the first preset threshold, the processor obtains the maximum horizontal and maximum vertical dimensions of the contour shape formed by the current depth detection points in the current scene data of the group.

[0123] Step S520: When the ratio between the maximum horizontal dimension and the maximum vertical dimension meets the second preset condition, the current detection shape is confirmed as a valid detection shape.

[0124] The processor calculates the ratio of the maximum horizontal dimension to the maximum vertical dimension to obtain the distance ratio. It then compares the distance ratios and determines that the user has extended their arm into the preset recognition area when the distance ratio meets the second preset condition. In this way, the current detection shape is confirmed as a valid detection shape.

[0125] For example, such as Figure 12 As shown, the processor performs ratio processing on the maximum horizontal dimension L and the maximum vertical dimension D. When the ratio of the maximum horizontal dimension L divided by the maximum vertical dimension D is greater than 5, or when the ratio of the maximum vertical dimension D divided by the maximum horizontal dimension L is greater than 5, it is determined that the user has extended his arm into the recognition area, and the current detection shape is confirmed as a valid detection shape, thereby realizing the object shape recognition within the preset recognition area.

[0126] In one embodiment, such as Figure 6 As shown, a method for controlling a projected image is provided, which can be applied to... Figure 1 Taking the processor in the example, the explanation includes the following steps:

[0127] Step S610: Acquire multiple sets of current scene data of the preset recognition area and the initial scene data of the preset recognition area in a time sequence; the initial scene data includes the initial depth information of multiple detection points, and the current scene data includes the current depth information of multiple detection points.

[0128] For a detailed explanation of step S610, please refer to the description of the above embodiments, which will not be repeated here.

[0129] Step S620: Perform numerical comparison processing on the initial scene data and multiple sets of current scene data to obtain the comparison result; and take the detection point corresponding to the comparison result that meets the first preset condition as the current depth detection point.

[0130] For a detailed explanation of step S620, please refer to the description of the above embodiments, which will not be repeated here.

[0131] Step S630: When the number of current depth detection points in the current scene data exceeds the first preset threshold, perform shape recognition on the current depth detection points in the current scene data and confirm the shapes that meet the second preset conditions as valid detection shapes.

[0132] For a detailed explanation of step S630, please refer to the description of the above embodiments, which will not be repeated here.

[0133] Step S640: If the number of confirmed valid detection shapes meets the fourth preset threshold, and the acquisition time interval of the current scene data corresponding to the confirmed valid detection shapes is within a preset time, then the current motion trajectory is obtained based on the specific detection points in the multiple sets of corresponding current scene data; the specific detection points are obtained based on the current detection points.

[0134] Considering that too few valid detection shapes may lead to misoperation, resulting in increased errors in motion trajectory judgment in subsequent steps; in addition, considering that the acquisition time interval of the current scene data is too long or too short may also lead to misoperation, resulting in increased errors in motion trajectory judgment in subsequent steps, for example, if the acquisition time interval of the current scene data is too long to reach the required number of valid detection shapes, it means that the user may put their hand into the preset recognition area and then quickly move it out and then move it back in, which can be judged as a misoperation.

[0135] To avoid the aforementioned erroneous operations and further improve the accuracy of projected image control, the processor needs to determine whether the number of valid detection shapes meets the quantity requirement and whether the acquisition time interval of the current scene data corresponding to the valid detection shapes meets the time requirement. Specifically, the processor can determine whether the number of valid detection shapes meets the fourth preset threshold. If the number of valid detection shapes meets the fourth preset threshold, it further determines whether the acquisition time interval of the current scene data corresponding to the valid detection shapes is within a preset time. If the acquisition time interval of the current scene data corresponding to the valid detection shapes is within the preset time, the current motion trajectory is obtained based on specific detection points in multiple sets of corresponding current scene data.

[0136] Specifically, the specific probe points in the current scene data are obtained based on the current probe points. For example, the processor identifies the coordinates of all current probe points in each set of current scene data, and the coordinates of the specific probe point in the xy plane can be the average of the x-coordinates and the average of the y-coordinates of all current probe points in each set of current scene data.

[0137] Step S650: Generate screen operation instructions based on the current motion trajectory.

[0138] For a detailed explanation of step S650, please refer to the description of the above embodiments, which will not be repeated here.

[0139] In the above embodiments, by identifying valid detection shapes in a preset recognition area, determining whether the number of valid detection shapes meets the quantity requirement, and determining whether the acquisition time interval of the current scene data corresponding to the valid detection shape meets the time requirement, when the quantity and time requirements are met, the current motion trajectory of the corresponding valid detection shape is obtained, and then screen operation instructions are generated based on the current motion trajectory. Thus, the user can operate the selection box of the projected screen based on gestures, further improving the accuracy of the projected screen control and realizing the control of the function box in the projected screen. This can bring convenience to the user in interacting with the projected screen, without the need for special interaction devices, with low cost and no limitation on the size of the projected screen, solving the problem of difficult touch operation in large-screen projection, and making it more convenient for users to operate the screen.

[0140] In one embodiment, such as Figure 7 As shown, if the number of confirmed valid detection shapes meets the fourth preset threshold, and the acquisition time interval of the current scene data corresponding to the confirmed valid detection shapes is within a preset time, then the steps to obtain the current motion trajectory based on specific detection points in multiple sets of corresponding current scene data include:

[0141] Step S710: Obtain the detection point data group corresponding to the effective detection shape, and transmit the detection point data group to the first queue in sequence; the detection point data group includes the spatial data of each current depth detection point corresponding to the effective detection shape.

[0142] An effective detection shape is formed by detection points from a set of detection point data groups. In some examples, the detection point data group includes the detection point number and the 3D spatial coordinates of the detection point. Each set of detection point data groups corresponds to an effective detection shape, and each effective detection shape corresponds to one frame of current scene data. The spatial data of the current depth detection point refers to the current depth information of the corresponding detection point, such as the 3D spatial coordinates of the corresponding detection point.

[0143] The processor can sequentially transmit the acquired detection point data sets corresponding to the valid detection shapes to the first queue based on timing.

[0144] Step S720: If the number of detection point data groups in the first queue meets the fourth preset threshold, and the interval input time between the first group and the last group of detection point data groups reaches the preset time when the fourth preset threshold is met, then the current motion trajectory is obtained based on the spatial data of specific detection points in each group of detection point data.

[0145] Considering that the number of detection point data groups in the first queue is too small, there may be erroneous operations, which will increase the error in motion trajectory judgment in subsequent steps; in addition, considering that the interval input time of the detection point data groups is too large or too small, it is easy to have erroneous operations, which will increase the error in motion trajectory judgment in subsequent steps. For example, if the interval input time of the detection point data groups is too long to reach the required number of detection point data groups, it means that the user may put his hand into the preset recognition area and then quickly move it out and then move it in again, which can be judged as an erroneous operation.

[0146] To avoid the aforementioned erroneous operations and further improve the accuracy of projected image control, the processor needs to determine whether the number of probe point data groups meets the quantity requirement and whether the interval input time of the probe point data groups meets the time requirement. Specifically, the processor can determine whether the number of probe point data groups in the first queue meets the fourth preset threshold. If the number of probe point data groups in the first queue meets the fourth preset threshold, it further determines whether the interval input time of the first and last probe point data groups is within a preset time. If the interval input time of the first and last probe point data groups is within the preset time, the current motion trajectory is obtained based on the spatial data of specific probe points in each probe point data group.

[0147] For example, the spatial data of a specific probe point can be the average of the x-coordinates and the average of the y-coordinates of all current probe points in each set of probe point data.

[0148] In one example, after the step of acquiring the detection point data group corresponding to the valid detection shape and sequentially transmitting the detection point data group to the first queue, the method includes: if the number of detection point data groups in the first queue is less than a fourth preset threshold each time a preset time is reached, then the detection point data groups in the first queue are cleared.

[0149] For example, when the number of probe point data groups in the first queue is less than the fourth preset threshold, the processor clears the probe point data groups in the first queue. Furthermore, the processor acquires newly added probe point data groups corresponding to the valid probe shape and transmits the newly added probe point data groups sequentially to the cleared first queue.

[0150] In one example, after the step of obtaining the detection point data group corresponding to the valid detection shape and transmitting the detection point data group sequentially to the first queue, the following steps are included: if the interval input time between the first group and the last group of detection point data groups in the first queue that meets the fourth preset threshold exceeds the preset time, then the detection point data group in the first queue is cleared.

[0151] For example, if the interval between the first and last sets of probe point data in the first queue exceeds a preset time when the processor meets the fourth preset threshold, the probe point data in the first queue is cleared. Furthermore, the processor obtains the newly added probe point data sets corresponding to the valid probe shape and transmits the newly added probe point data sets sequentially to the cleared first queue, thereby avoiding invalid data from occupying queue memory.

[0152] In one embodiment, such as Figure 8 As shown, the steps to obtain the current motion trajectory based on specific detection points in multiple sets of corresponding current scene data include:

[0153] Step S810: Obtain the location information of specific detection points in multiple sets of current scene data corresponding to the effective detection shape in a time sequence.

[0154] The specific detection point location information is the average of the x-coordinates and the average of the y-coordinates of all current detection points in each set of current scene data.

[0155] Step S820: Based on the acquisition timing of the current scene data of each corresponding valid detection shape, if the coordinate values ​​of each specific detection point position information in the first spatial direction are increasing or decreasing, and the maximum coordinate change value in the position information of each specific detection point is greater than the fifth preset threshold, the current motion trajectory is determined to be a trajectory moving along the first spatial direction.

[0156] Based on the acquisition timing of current scene data for each corresponding valid probe shape, the processor determines the movement trend of the position information of each specific probe point in the first spatial direction, and thus determines the target operation direction. For example, Figure 14 As shown, the first spatial direction is the X-axis direction. If the position information of each specific detection point (such as...) Figure 14 In the first spatial direction, if the coordinate values ​​of specific detection points 1, 2, and 3 decrease, and the maximum coordinate change value in the position information of each specific detection point is greater than a fifth preset threshold, then the current motion trajectory is determined to be moving in the negative direction of the X-axis. Conversely, if the coordinate values ​​of the position information of each specific detection point increase in the first spatial direction, and the maximum coordinate change value in the position information of each specific detection point is greater than a fifth preset threshold, then the current motion trajectory is determined to be moving in the positive direction of the X-axis.

[0157] Step S830: Based on the acquisition timing of the current scene data of each corresponding valid detection shape, if the coordinate values ​​of each specific detection point position information in the second spatial direction are increasing or decreasing, and the maximum coordinate change value in each specific detection point position information is greater than the sixth preset threshold, the current motion trajectory is determined to be a trajectory moving along the second spatial direction.

[0158] Based on the acquisition timing of current scene data for each corresponding valid detection shape, the processor determines the movement trend of the position information of each specific detection point in the second spatial direction, and thus determines the target operation direction. For example, if the second spatial direction is the Y-axis, and the coordinate values ​​of the position information of each specific detection point in the second spatial direction are decreasing, and the maximum coordinate change value in the position information of each specific detection point is greater than a sixth preset threshold, then the current motion trajectory is determined to be moving in the negative direction of the Y-axis. Conversely, if the coordinate values ​​of the position information of each specific detection point in the second spatial direction are increasing, and the maximum coordinate change value in the position information of each specific detection point is greater than a sixth preset threshold, then the current motion trajectory is determined to be moving in the positive direction of the Y-axis.

[0159] Step S840: When the maximum coordinate change value in the position information of each specific detection point in the third spatial direction is greater than the seventh preset threshold, the current motion trajectory is determined to be a trajectory moving along the third spatial direction.

[0160] Based on the timing of acquiring current scene data for each corresponding valid detection shape, the processor determines the movement trend of the position information of each specific detection point in the third spatial direction, and then determines the target operation direction. For example, if the third spatial direction is the Z-axis direction, and the maximum coordinate change value in the position information of each specific detection point is greater than the seventh preset threshold, then the current motion trajectory is determined to be a movement along the Z-axis direction, that is, it is considered that the user's arm has moved accordingly in the Z-axis direction.

[0161] In one example, if the coordinate values ​​of specific detection point locations in the second spatial direction first decrease and then increase, or first increase and then decrease, it is considered a misoperation, and the user's arm movement in that direction is disregarded. Figure 14 The Y-axis coordinate value in the data first increased and then decreased.

[0162] In one example, if the X-axis, Y-axis, and Z-axis directions do not meet the above conditions, the corresponding current scene data will be identified as invalid data.

[0163] In one example, the steps for sequentially acquiring the location information of specific probe points in multiple sets of current scene data corresponding to valid probe shapes include:

[0164] The spatial coordinates of the current depth detection point in the current scene data corresponding to the effective detection shape are obtained in a time sequence; the spatial coordinates of the current depth detection point in each set are averaged to obtain the specific detection point position information corresponding to the effective detection shape.

[0165] The spatial coordinates of the corresponding current depth detection point can be coordinates in the xy plane. For example, the spatial coordinates of each group of current depth detection points can be the average of the x-coordinates and the average of the y-coordinates of each group of current depth detection points.

[0166] In one example, the steps for sequentially acquiring the location information of specific probe points in multiple sets of current scene data corresponding to valid probe shapes include:

[0167] The spatial coordinates of the current depth detection point in the current scene data corresponding to the effective detection shape are obtained in a time sequence; the coordinates of the current depth detection point with the largest or smallest coordinate value in the first direction are used as the specific detection point position information of the effective detection shape.

[0168] Specifically, the coordinates of the current depth detection point with the largest coordinate value in the first direction are identified as the rightmost detection point among all current depth detection points in each set of current scene data corresponding to the effective detection shape. The coordinates of the current depth detection point with the smallest coordinate value in the first direction are identified as the leftmost detection point among all current depth detection points in each set of current scene data corresponding to the effective detection shape. In other words, a specific detection point can be either the leftmost or rightmost current depth detection point in each set of current scene data corresponding to the effective detection shape.

[0169] For example, such as Figure 16 and Figure 17 Within the detection area, there are two preset recognition areas (S1 and S2). When the number and time requirements are met for the effective detection shapes obtained from the right-hand preset recognition area S2, the specific detection point location information of this set of effective detection shapes is the location information of the leftmost (i.e., the effective detection point with the smallest x-coordinate value) effective detection point. When the number and time requirements are met for the effective detection shapes obtained from the left-hand preset recognition area S1, the specific detection point location information of this set of effective detection shapes is the location information of the rightmost (i.e., the effective detection point with the largest x-coordinate value) effective detection point.

[0170] In one embodiment, the number of preset recognition regions is at least two; the step of obtaining initial scene data for the preset recognition regions includes:

[0171] Acquire human feature location data in the detection area; compare the human feature location data with each preset recognition area, and based on the comparison results, acquire the initial scene data of the preset recognition area that is close to the human feature location data.

[0172] The detection module detects the human feature location data in the detection area and transmits the data to the processor, which then obtains the human feature location data of the detection area. The processor compares the human feature location data with each preset recognition area, and based on the comparison results, obtains the initial scene data of the preset recognition area closest to the human feature location data. The remaining preset recognition areas are not processed further, which can further reduce the program's computational burden and speed up the response efficiency.

[0173] For example, such as Figure 16 In the initial projection area, two preset recognition areas, S1 and S2, are defined. Both S1 and S2 are within the initial projection area, with S1 located in the lower left corner of the projected image and S2 located in the lower right corner of the person's image. The detection module detects the human body feature position data within the initial projection area to determine whether the user's body is located in the left or right half of the initial projection area. Based on this determination, only the corresponding side of the preset recognition area is processed for valid detection shape recognition and the current motion trajectory of the corresponding valid detection shape. This further reduces the computational burden on the program and accelerates response efficiency.

[0174] In one embodiment, prior to the step of acquiring multiple sets of current scene data for a preset recognition region in a time sequence, the following steps are included:

[0175] Receive screen operation requests and generate gesture operation indicator boxes in the projection screen area corresponding to the preset recognition area according to the screen operation requests.

[0176] For example, when the program detects an operation command event reported within a preset recognition area, a gesture operation prompt box pops up in the corresponding projection screen area to guide and interact with the user. This may include forming a gesture operation prompt box within the portion of the projection screen corresponding to the preset recognition area, prompting the user to perform a gesture operation within that prompt box. If the program detects no data input within the preset recognition area for more than a first preset time (e.g., 5 seconds), the gesture operation prompt box is hidden to avoid interfering with normal user operation, thereby improving the user experience.

[0177] In one embodiment, such as Figure 9 As shown, the specific implementation process of the projection screen control method is as follows:

[0178] Step 1: Read scene data (including initial scene data and multiple sets of current scene data); where scene data is environmental data collected by the detection module. The detection module is used to detect depth information in the environment. The collected data includes three-dimensional spatial data of a large number of discrete detection points within the detection range.

[0179] Step 2: Extract the 3D spatial data from the preset recognition area in the initial scene data.

[0180] Step 3: Save the current depth information of the initial scene data. In Step 3, either a single frame of 3D spatial data from the preset recognition area can be acquired, or multiple frames can be acquired and the depth data of corresponding points in each frame can be averaged. These depth data corresponding to each detection point are then saved and denoted as the initial depth data A0 for each detection point. This Step 3 performs initial calibration of the environmental space. It should be noted that the user should not be within the detection range of the detection module during Step 3, at least not within the preset recognition area. The initial scene calibration is to compare with scene data containing gestures in subsequent steps to determine which detection points have changed their depth data, thereby determining whether an object has entered the preset recognition area.

[0181] Step 4: Extract the current depth data Ai from the preset recognition area in the current scene data (used to recognize user gestures). This step is executed in the same way as step 2 above, but its main purpose is to capture user gestures within the recognition area, not for calibration. When executing this step, it is not necessary to consider whether a user is present within the overall detection range; the step is executed regardless of their presence. This step can obtain the 3D spatial data (i.e., the current depth data Ai) for each frame through the detection module, or it can obtain the 3D spatial data once at preset frame intervals (e.g., every 3 frames).

[0182] Step 5: Compare and judge the initial scene data with the current scene data of each group. Specifically, Step 5 compares the current depth data obtained in Step 4 with the initial depth data in Step 3, performs a difference calculation on the depth information of each detection point, and obtains the depth change of each detection point relative to the initial scene, denoted as △ENV. Then, △ENV = |Ai - A0|. Record the current depth detection points K1 that have a △ENV greater than the first preset value, and count the number of current depth detection points K1. If the number of current depth detection points K1 is greater than the second preset value, then the data of each frame of current depth detection point K1 that meets the above condition is pushed to the next execution step; otherwise, it is considered invalid data. Figure 11 As shown, Figure 11 The discrete points in the diagram represent the detection points covering the user, while the discrete points in the preset identification area are nitrogen depth detection points that meet the above conditions.

[0183] Step 6: Identify the object shape; based on the △ENV determined in Step 5, determine whether the shape it forms conforms to the preset shape (such as an arm shape).

[0184] Step 7: Based on timing, transmit each frame of △ENV data that meets the shape recognition requirements to the first queue. For example... Figure 13As shown, the first queue includes data 1, array 2, array 3, array 4 and array 5, etc. Each set of data in the first queue (denoted as △ENV-n) contains three-dimensional spatial data of each detection point in a preset recognition area where △ENV is not zero.

[0185] Step 8: Determine whether the newly added data array in the first queue meets the quantity requirement, and whether the time requirement is met if the quantity requirement is met.

[0186] Step 9: When the conditions in step 8 are met, combine the data in the newly added data group to identify the motion trajectory and obtain the current motion trajectory.

[0187] Step 10: Based on the determined current motion trajectory, output the corresponding operation command to the operating system. For example, when step 9 detects that the user's arm is moving towards -x, output a command to move the selection box to the left; when it detects that the user's arm is moving towards +x, output a command to move the selection box to the right; when it detects that the user's arm is moving towards -y, output a command to move the selection box down (e.g., ...). Figure 15 (as shown); when the user's arm moves to +y, the command to move the selection box up is output; when the user's arm moves in the z direction, the command to click or confirm is output; after the command is output, the corresponding array data is cleared, and the new array in the first queue is re-identified starting from step 8.

[0188] In the above embodiments, by identifying valid detection shapes in a preset recognition area, determining whether the number of valid detection shapes meets the quantity requirement, and determining whether the acquisition time interval of the current scene data corresponding to the valid detection shape meets the time requirement, when the quantity and time requirements are met, the current motion trajectory of the corresponding valid detection shape is obtained, and then screen operation instructions are generated based on the current motion trajectory. Thus, the user can operate the selection box of the projected screen based on gestures, further improving the accuracy of the projected screen control and realizing the control of the function box in the projected screen. This can bring convenience to the user in interacting with the projected screen, without the need for special interaction devices, with low cost and no limitation on the size of the projected screen, solving the problem of difficult touch operation in large-screen projection, and making it more convenient for users to operate the screen.

[0189] It should be understood that, although Figures 2 to 9 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figures 2 to 9At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0190] In one embodiment, such as Figure 18 As shown, a projection device is provided, including a detection module 120 and a processor 110. The detection module 120 is connected to the processor 110. The processor 110 is used to execute the steps of any of the above-described control methods for projecting images.

[0191] The projection device can be a projector, the processor 110 can be the main processor 110 of the projector, and the detection module 120 can be a lidar module, for example, a planar array lidar ranging module. The detection module 120 may include a TOF sensor. The detection module 120 can be used to project a detection array onto the detection area. For specific descriptions of the control methods for the projected image, please refer to the description of the above embodiments; they will not be repeated here.

[0192] In the above embodiments, the processor 110 sequentially acquires multiple sets of current scene data of a preset recognition area and initial scene data of the preset recognition area; the initial scene data includes initial depth information of multiple detection points, and the current scene data includes current depth information of multiple detection points; the initial scene data and multiple sets of current scene data are numerically compared to obtain a comparison result; and the detection point corresponding to the comparison result satisfying the first preset condition is taken as the current depth detection point; when the number of current depth detection points in the current scene data exceeds the first preset threshold, shape recognition is performed on the current depth detection points in the set of current scene data, and the shape satisfying the second preset condition is confirmed as a valid detection shape; the current motion trajectory is obtained based on the current depth detection points in the current scene data corresponding to multiple sets of valid detection shapes; and screen operation instructions are generated based on the current motion trajectory, thereby realizing convenient control of the projected screen. This application identifies valid detection shapes and their current motion trajectories within a preset recognition area, and then generates screen operation commands based on the current motion trajectory. This allows users to operate the selection boxes on the projected screen using gestures, thereby controlling the function boxes on the projected screen. This provides users with convenient interaction with the projected screen, eliminates the need for dedicated interaction devices, reduces costs, and is not limited by the size of the projected screen. It solves the problem of difficult touch operation in large-screen projection and makes it easier for users to control the screen.

[0193] In one embodiment, this application provides a computer storage medium storing a computer program thereon, wherein the computer program, when executed by a processor, implements the steps of the control method for the projected image described above.

[0194] In one example, when a computer program is executed by a processor, it performs the following steps:

[0195] The system acquires multiple sets of current scene data and initial scene data of a preset recognition area in a sequential manner. The initial scene data includes initial depth information of multiple detection points, and the current scene data includes current depth information of multiple detection points. The initial scene data and multiple sets of current scene data are numerically compared to obtain a comparison result. The detection point corresponding to the comparison result that satisfies the first preset condition is taken as the current depth detection point. When the number of current depth detection points in the current scene data exceeds the first preset threshold, shape recognition is performed on the current depth detection points in the set of current scene data, and the shape that satisfies the second preset condition is confirmed as a valid detection shape. The current motion trajectory is obtained based on the current depth detection points in the current scene data corresponding to multiple sets of valid detection shapes. Based on the current motion trajectory, screen operation instructions are generated to achieve convenient control of the projected screen.

[0196] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the division operations described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM) and programmable ROM (PROM).

Claims

1. A method for controlling a projected image, characterized in that, Includes the following steps: Acquire multiple sets of current scene data for a preset recognition region in a time sequence, and acquire the initial scene data for the preset recognition region; The initial scene data includes initial depth information of multiple detection points, and the current scene data includes current depth information of multiple detection points; The initial scene data is compared numerically with multiple sets of current scene data to obtain a comparison result. The detection point corresponding to the comparison result satisfying the first preset condition is taken as the current depth detection point; When the number of current depth detection points in the current scene data exceeds a first preset threshold, shape recognition is performed on the current depth detection points in the current scene data, and shapes that meet the second preset condition are confirmed as valid detection shapes. The current motion trajectory is obtained based on the current depth detection point in the current scene data corresponding to multiple sets of effective detection shapes; Based on the current motion trajectory, generate screen operation instructions.

2. The method for controlling the projected image according to claim 1, characterized in that, Before the steps of acquiring multiple sets of current scene data of the preset recognition area in a time sequence and acquiring the initial scene data of the preset recognition area, the following are included: Obtain the detection area and the initial projection area located within the detection area; Based on the detection area and the initial projection area, a recognition area is selected to obtain the preset recognition area; the preset recognition area is located on the lower side of the initial projection area and / or the lower side of the detection area.

3. The method for controlling the projected image according to claim 1, characterized in that, Before acquiring multiple sets of current scene data for the preset recognition region in a time sequence and acquiring the initial scene data for the preset recognition region, the method further includes the following steps: Acquire second current scene data within a preset recognition area; when the change between the second current scene data and the initial scene data within the preset recognition area is greater than a second preset threshold, update the second current scene data to the initial scene data; and / or Obtain the device's motion change parameters; when the motion change parameters are greater than a third preset threshold, obtain the second current scene data within a preset recognition area, and update the second current scene data to the initial scene data.

4. The method for controlling the projected image according to claim 1, characterized in that, When the number of current depth detection points in the current scene data exceeds a first preset threshold, the step of performing shape recognition on the current depth detection points in the current scene data set and confirming shapes that meet a second preset condition as valid detection shapes includes: When the number of current depth detection points in the current scene data exceeds a first preset threshold, the contour shape formed by the current depth detection points in the current scene data is identified to obtain the current detection shape. Based on a gesture recognition database, the current detected shape is matched, and when the matching result meets a second preset condition, the current detected shape is confirmed as the valid detected shape; or... When the number of current depth detection points in the current scene data exceeds a first preset threshold, the maximum horizontal and maximum vertical dimensions of the contour shape formed by the current depth detection points in the current scene data are obtained; when the ratio between the maximum horizontal dimension and the maximum vertical dimension satisfies a second preset condition, the current detection shape is confirmed as the valid detection shape.

5. The method for controlling the projected image according to claim 1, characterized in that, The step of obtaining the current motion trajectory based on the current depth detection points in the current scene data corresponding to multiple sets of effective detection shapes includes: If the number of confirmed valid detection shapes meets a fourth preset threshold, and the acquisition time interval of the current scene data corresponding to the confirmed valid detection shapes is within a preset time, then the current motion trajectory is obtained based on specific detection points in multiple sets of corresponding current scene data; the specific detection points are obtained based on the current depth detection points.

6. The method for controlling the projected image according to claim 5, characterized in that, The step of obtaining the current motion trajectory based on specific detection points in multiple sets of corresponding current scene data when the number of confirmed valid detection shapes meets a fourth preset threshold and the acquisition time interval of the current scene data corresponding to the confirmed valid detection shapes is within a preset time includes: Acquire a set of detection point data corresponding to the effective detection shape, and transmit the set of detection point data to the first queue in sequence; the set of detection point data includes spatial data of each current depth detection point corresponding to the effective detection shape. If the number of the detection point data groups in the first queue meets the fourth preset threshold, and the interval input time of the first group and the last group of detection point data groups reaches the preset time, then the current motion trajectory is obtained based on the spatial data of a specific detection point in each group of detection point data groups.

7. The method for controlling the projected image according to claim 6, characterized in that, After the step of acquiring the detection point data group corresponding to the effective detection shape and sequentially transmitting the detection point data group to the first queue, the following is included: If, at each time the preset time is reached, the number of probe point data groups in the first queue is less than the fourth preset threshold, then the probe point data groups in the first queue are cleared; or If the interval between the first group and the last group of the probe point data in the first queue that meets the fourth preset threshold exceeds a preset time, then the probe point data in the first queue is cleared.

8. The method for controlling the projected image according to claim 5, characterized in that, The step of obtaining the current motion trajectory based on specific detection points in multiple sets of corresponding current scene data includes: Acquire the location information of specific detection points in the current scene data corresponding to the effective detection shape in a time sequence; Based on the acquisition sequence of the current scene data of each corresponding effective detection shape, if the coordinate values ​​of the position information of each specific detection point in the first spatial direction are increasing or decreasing, and the maximum coordinate change value in the position information of each specific detection point is greater than the fifth preset threshold, the current motion trajectory is determined to be a trajectory moving along the first spatial direction. Based on the acquisition sequence of the current scene data of each corresponding effective detection shape, if the coordinate values ​​of the position information of each specific detection point in the second spatial direction are increasing or decreasing, and the maximum coordinate change value in the position information of each specific detection point is greater than the sixth preset threshold, the current motion trajectory is determined to be a trajectory moving along the second spatial direction. When the maximum coordinate change value in the position information of each specific detection point in the third spatial direction is greater than the seventh preset threshold, the current motion trajectory is determined to be a trajectory moving along the third spatial direction.

9. The method for controlling the projected image according to claim 8, characterized in that, The step of acquiring the location information of specific detection points in the current scene data corresponding to the effective detection shape in a time sequence includes: The spatial coordinates of the current depth detection point in the current scene data corresponding to the effective detection shape are obtained in a time sequence. The spatial coordinates of each group of current depth detection points are averaged to obtain the specific detection point location information corresponding to the effective detection shape; or, The spatial coordinates of the current depth detection point in the current scene data corresponding to the effective detection shape are obtained in a time sequence. The coordinates of the current depth detection point with the largest or smallest coordinate value in the first direction are used as the specific detection point position information of the effective detection shape of the group.

10. The method for controlling the projected image according to claim 2, characterized in that, The number of preset recognition regions is at least two; the preset recognition regions are located within the overlapping area formed by the left 1 / 3 and the lower 1 / 2 of the initial projection region, and / or within the overlapping area formed by the right 1 / 3 and the lower 1 / 2 of the initial projection region; the step of obtaining the initial scene data of the preset recognition regions includes: Acquire human feature location data within the detection area; The human body feature location data is compared with each of the preset recognition regions, and based on the comparison results, the initial scene data of the preset recognition regions that are close to the human body feature location data is obtained.

11. The method for controlling the projected image according to claim 1, characterized in that, Before the step of acquiring multiple sets of current scene data for a preset recognition area in a time sequence, the following steps are included: Receive a screen operation request, and generate a gesture operation indicator box in the projection screen area corresponding to the preset recognition area according to the screen operation request.

12. A projection device, characterized in that, It includes a detection module and a processor, wherein the detection module is connected to the processor; The processor is used to perform the steps of the control method for the projected image as described in any one of claims 1 to 11.

Images