Object standardization drawing method, device and equipment for accident scene and medium
By using automatic identification and symbol adjustment based on high-density point cloud data, the problems of data accuracy and drawing standardization in traditional traffic accident scene investigation have been solved, enabling fast, accurate, and standardized drawing.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- REALSEE (BEIJING) TECHNOLOGY CO LTD
- Filing Date
- 2026-04-03
- Publication Date
- 2026-06-26
AI Technical Summary
In traditional traffic accident scene investigations, manual measurement leads to inconsistent data accuracy, low drawing efficiency, and difficulty in standardizing drawing procedures.
Based on high-density point cloud data, the shape and size of objects at the accident scene are automatically identified, initial object symbols are determined, and they are adjusted to match the actual objects, thus achieving automated drawing.
It enables the rapid, accurate, and standardized drawing of accident scene diagrams, improving drawing accuracy and efficiency, reducing manual labor, and shortening drawing time.
Smart Images
Figure CN122289446A_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the field of intelligent transportation, and in particular to a method, apparatus, equipment, and medium for the standardized drawing of objects at accident scenes. Background Technology
[0002] In traffic accident scene investigation, the industry still widely uses traditional methods such as camera photography and manual measurement with tape measures to complete on-site data collection and accident scene mapping. Under this traditional investigation model, key physical parameters such as distances and dimensions at the scene are obtained by manual point-by-point measurement. This not only involves a large workload and is time-consuming, but manual operation is also easily affected by factors such as the scene environment and operator experience, resulting in inconsistent data accuracy. At the same time, the drawing of the scene map also relies on manual work by the investigators, which leads to problems such as low drawing efficiency and difficulty in standardizing drawing, and is prone to non-standard situations such as deviations in the labeling of scene elements and inaccurate scale. Summary of the Invention
[0003] To address the aforementioned technical problems, this disclosure is proposed. Embodiments of this disclosure provide a method, apparatus, device, and medium for standardized object drawing of accident scenes.
[0004] According to one aspect of the present disclosure, a method for standardized drawing of objects at an accident scene is provided, comprising: Based on high-density point cloud data of the target accident site, a top-down view of the target is determined; Identify the size of the target object in the top view of the target, as well as the category and / or shape of the target object; Determine the initial object symbol corresponding to the target object based on the category and / or shape of the target object; The size of the initial object symbol is adjusted according to the size of the target object to obtain the target symbol of the target object in the target top view.
[0005] Optionally, it also includes: The target symbol is adjusted accordingly based on at least one received adjustment instruction to obtain the adjusted target symbol.
[0006] Optionally, the step of adjusting the target symbol according to at least one received adjustment instruction to obtain the adjusted target symbol includes: Receive the at least one adjustment instruction, and determine at least one corresponding adjustment operation based on the at least one adjustment instruction; the at least one adjustment operation includes at least one of the following: rotation, translation, scaling, and changing aspect ratio; At least one adjustment operation is performed on the target object symbol in a preset order to obtain the adjusted target symbol.
[0007] Optionally, after determining the target top view based on the high-density point cloud of the target accident scene, the method further includes: The location information of the target object is determined based on the point cloud data corresponding to the target object; The orientation of the target object is determined based on its shape.
[0008] Optionally, adjusting the size of the initial object symbol according to the size of the target object to obtain the target symbol corresponding to the target object includes: According to the location information of the at least one target object, the at least one initial object symbol is inserted into the top view of the target to obtain at least one initial object symbol; The at least one initial object symbol is stretched according to the orientation of the at least one target object until the length of the initial object symbol matches the size of the target object, thus obtaining the target symbol.
[0009] Optionally, determining the initial object symbol corresponding to the target object based on the category and / or shape of the target object includes: Based on the scene type corresponding to the target accident scene, a corresponding target symbol set is determined; each scene type corresponds to a symbol set, and the symbol set includes multiple preset object symbols of different objects; Based on the category and / or shape of the target object, multiple preset object symbols in the target symbol set are matched to determine the preset object symbol that matches the shape of the target object as the initial object symbol.
[0010] Optionally, determining the target top view based on high-density point cloud data of the target accident scene includes: Point cloud data is collected from the target accident site to obtain the high-density point cloud data; The three-dimensional high-density point cloud data is mapped onto a two-dimensional top-view plane to obtain the target top view.
[0011] According to another aspect of the embodiments of this disclosure, an apparatus for standardizing and drawing objects at an accident scene is provided, comprising: The data acquisition module is used to determine the top view of the target based on high-density point cloud data of the target accident site; The target recognition module is used to identify the shape and size of the target object in the top view of the target; A symbol determination module is used to determine the initial object symbol corresponding to the target object based on the shape of the target object; The symbol adjustment module is used to adjust the size of the initial object symbol according to the size of the target object, so as to obtain the target symbol of the target object in the target top view.
[0012] Optionally, the device further includes: The instruction adjustment module is used to adjust the target symbol according to at least one received adjustment instruction to obtain the adjusted target symbol.
[0013] Optionally, the instruction adjustment module is specifically used to receive the at least one adjustment instruction and determine at least one corresponding adjustment operation based on the at least one adjustment instruction; the at least one adjustment operation includes at least one of the following: rotation, translation, scaling, and changing aspect ratio; the at least one adjustment operation is sequentially performed on the target object symbol in a preset order to obtain the adjusted target symbol.
[0014] Optionally, the device further includes: The position orientation module is used to determine the position information and orientation of the target object based on the point cloud data corresponding to the target object.
[0015] Optionally, the symbol adjustment module is specifically used to insert the at least one initial object symbol into the target top view according to the position information of the at least one target object to obtain at least one initial object symbol; and to perform stretching processing on the at least one initial object symbol according to the orientation of the at least one target object until the length of the initial object symbol matches the size of the target object to obtain the target symbol.
[0016] Optionally, the symbol determination module is specifically used to determine a corresponding target symbol set according to the scene type corresponding to the target accident scene; each scene type corresponds to a symbol set, and the symbol set includes multiple preset object symbols of different objects; based on the category and / or shape of the target object, the preset object symbol that matches the shape of the target object is determined as the initial object symbol.
[0017] Optionally, the data acquisition module is specifically used to collect point cloud data of the target accident site to obtain high-density point cloud data; and to map the three-dimensional high-density point cloud data onto a two-dimensional top-view plane to obtain a top view of the target.
[0018] According to another aspect of the present disclosure, an electronic device is provided, comprising: Memory, used to store computer program products; The processor is configured to execute a computer program product stored in the memory, and when the computer program product is executed, to implement the object normalization drawing method for accident scenes as described in any of the above embodiments.
[0019] According to another aspect of the present disclosure, a computer-readable storage medium is provided that stores computer program instructions thereon, which, when executed by a processor, implement the object standardization drawing method for accident scenes described in any of the above embodiments.
[0020] According to another aspect of the present disclosure, a computer program product is provided, including computer program instructions that, when executed by a processor, implement the object normalization drawing method for accident scenes described in any of the above embodiments.
[0021] Based on the object standardization drawing method, apparatus, equipment, and medium for accident scenes provided in the above embodiments of this disclosure, a target top view is determined based on high-density point cloud data of the target accident scene; a top view of the accident scene is quickly and automatically acquired, providing a foundation for subsequent drawing of target objects; the shape and size of target objects in the target top view are identified; automatic identification improves the recognition efficiency of target objects, eliminating the need for manual measurement; an initial object symbol corresponding to the target object is determined based on the shape of the target object; by determining the initial object symbol for the target object, symbolization of the target object is achieved, avoiding shape differences caused by manual drawing, and unified management of object drawing is achieved through symbolization of the target object; the size of the initial object symbol is adjusted according to the size of the target object to obtain the target symbol of the target object in the target top view; by adjusting the initial object symbol based on the size, the adjusted target symbol matches the size of the target object, achieving accurate depiction of the target object based on objective data, ensuring the accuracy of the shape and size of drawing elements, and realizing the standardization of drawing.
[0022] The technical solutions of this disclosure will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description
[0023] The accompanying drawings, which form part of this specification, illustrate embodiments of this disclosure and, together with the description, serve to explain the principles of this disclosure.
[0024] This disclosure will become clearer with reference to the accompanying drawings and the following detailed description, wherein: Figure 1 This is a flowchart illustrating an exemplary embodiment of the present disclosure of a method for normalizing the drawing of objects at an accident scene; Figure 2 This is a flowchart illustrating the process of matching initial object symbols in a method provided by an exemplary embodiment of this disclosure; Figure 3 This is a schematic diagram illustrating the application of a method provided in an exemplary embodiment of this disclosure to a traffic accident scene; Figure 4 This is a flowchart illustrating the method for determining a target symbol provided in an exemplary embodiment of this disclosure; Figure 5 yes Figure 3 A schematic diagram illustrating the resizing of the initial object symbol in an exemplary embodiment shown; Figure 6 yes Figure 5 A schematic diagram showing the initial object symbol after size adjustment in the exemplary embodiment shown; Figure 7 This is a flowchart illustrating a method for normalizing the drawing of objects at an accident scene, provided in another exemplary embodiment of this disclosure. Figure 8 This is a flowchart illustrating the process of adjusting a target symbol in a method provided by another exemplary embodiment of this disclosure; Figure 9 This is a schematic diagram of the structure of an object normalization drawing device for an accident scene provided in an exemplary embodiment of this disclosure; Figure 10 A block diagram of an electronic device according to an embodiment of the present disclosure is shown. Detailed Implementation
[0025] Hereinafter, exemplary embodiments according to the present disclosure will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of the present disclosure, and not all embodiments of the present disclosure, and it should be understood that the present disclosure is not limited to the exemplary embodiments described herein.
[0026] It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values of the components and steps set forth in these embodiments do not limit the scope of this disclosure.
[0027] Those skilled in the art will understand that the terms "first," "second," etc., in the embodiments of this disclosure are only used to distinguish different steps, devices, or modules, and do not represent any specific technical meaning, nor do they indicate a necessary logical order between them.
[0028] It should also be understood that in the embodiments disclosed herein, "multiple" can refer to two or more, and "at least one" can refer to one, two or more.
[0029] It should also be understood that any component, data or structure mentioned in the embodiments of this disclosure can generally be understood as one or more unless expressly defined or given to the contrary in the context.
[0030] Furthermore, the term "and / or" in this disclosure is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this disclosure generally indicates that the preceding and following related objects have an "or" relationship. The data referred to in this disclosure can include unstructured data such as text, images, and videos, as well as structured data.
[0031] It should also be understood that the description of the various embodiments in this disclosure emphasizes the differences between the various embodiments, and the similarities or similarities can be referred to each other. For the sake of brevity, they will not be described in detail.
[0032] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.
[0033] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit this disclosure or its application or use.
[0034] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.
[0035] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.
[0036] The embodiments disclosed herein can be applied to electronic devices such as terminal devices, computer systems, and servers, and can operate together with a wide range of other general-purpose or special-purpose computing system environments or configurations. Examples of well-known terminal devices, computing systems, environments, and / or configurations suitable for use with electronic devices such as terminal devices, computer systems, and servers include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments including any of the above systems, etc.
[0037] Electronic devices such as terminal devices, computer systems, and servers can be described in the general context of computer system executable instructions (such as program modules) executed by a computer system. Typically, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in distributed cloud computing environments, where tasks are executed by remote processing devices linked through communication networks. In distributed cloud computing environments, program modules can reside on local or remote computing system storage media, including storage devices.
[0038] Exemplary methods Figure 1 This is a flowchart illustrating a method for normalizing the drawing of objects at an accident scene according to an exemplary embodiment of this disclosure. This embodiment can be applied to electronic devices, such as... Figure 1 As shown, it includes the following steps: Step 102: Determine the target top view based on the high-density point cloud data of the target accident site.
[0039] Optionally, this embodiment can scan the target accident scene using at least one sensor (e.g., LiDAR, depth camera, etc.) to obtain high-density three-dimensional point cloud data. Since the point cloud data contains three-dimensional coordinate information, a top-down view of the target accident scene can be obtained through operations such as top-down projection. Optionally, the target top-down view can be a rasterized top-down view or a real-scene top-down view. This embodiment rapidly acquires high-density point cloud data using mobile devices, obtaining a complete and accurate three-dimensional digital base map of the scene, providing a clear, accurate, and objective data source for all subsequent operations.
[0040] Optionally, the target accident scene can be a traffic accident scene, a production safety accident scene (an accident that occurs during production, construction, or operation), a public safety accident scene (an accident that occurs in public places or public facilities), an accident scene caused by natural disasters (e.g., accidents caused by natural factors such as earthquakes, floods, and typhoons), or other accident scenes in the transportation sector (accidents can occur in all areas of transportation except for road traffic accidents, such as railway accident scenes and water traffic accident scenes).
[0041] Step 104: Identify the size of the target object in the top view, as well as the category and / or shape of the target object.
[0042] In this embodiment, the target top view may include at least one target object, and at least one target object may be processed separately. Optionally, at least one target object may be processed sequentially, or at least one target object may be processed simultaneously.
[0043] Optionally, the target object can be any object at the target accident scene, such as vehicles, people, electric vehicles, road lines, etc.
[0044] In one embodiment, at least one target object included in the target top view can be identified by deep learning methods or other object recognition methods (e.g., connected component analysis). Optionally, the target top view can be semantically segmented by a semantic segmentation model to obtain a category label + object mask corresponding to at least one target object. The category corresponding to the target object can be directly determined based on the category label, and the shape and size of the target object can be determined by the shape and size of the mask. Optionally, by connected component analysis, the target top view is first binarized to obtain a binarized top view. Neighborhood connected component detection is performed on the binarized top view to output a mask + bounding rectangle corresponding to each target object. The size and shape of the target object can be determined based on the mask and the bounding rectangle.
[0045] Step 106: Determine the initial object symbol corresponding to the target object based on the category and / or shape of the target object.
[0046] In this embodiment, the initial object symbol can be selected from a pre-created set of multiple preset object symbols. For example, the set includes preset object symbols with category names and corresponding illustrations, such as trucks, cars, electric vehicles, and human bodies. The preset object symbol corresponding to the category of the target object can be determined as the initial object symbol. For example, if the category of the target object is electric vehicle, the preset object symbol with the category name "electric vehicle" in the set can be directly obtained as the initial object symbol of the target object. Alternatively, the shape of the target object can be matched with the shapes of multiple preset object symbols to obtain the preset object symbol with the matching shape as the initial object symbol of the target object. Optionally, when a unique initial object symbol cannot be determined based on either category or shape alone, it can be determined by combining the two. For example, when multiple preset object symbols are determined by searching based on category, the shape is then matched with the multiple preset object symbols to determine the unique preset object symbol with the matching shape as the initial object symbol.
[0047] Step 108: Adjust the size of the initial object symbol according to the size of the target object to obtain the target symbol of the target object in the top view of the target.
[0048] In this embodiment, the preset object symbols are usually set to a uniform size (smaller for easier display) for ease of management. However, this uniform size cannot fully match the target object. Therefore, this embodiment adjusts the size of the initial object symbols based on the size of the target object to obtain target symbols that match the size of the target object, thereby achieving a better standardized display of the target object in the drawing.
[0049] The method provided in the above embodiments of this disclosure determines a target top view based on high-density point cloud data of the target accident scene; it enables rapid and automatic acquisition of the top view of the accident scene, providing a foundation for subsequent drawing of the target object; it identifies the shape and size of the target object in the target top view; automatic identification improves the recognition efficiency of the target object, eliminating the need for manual measurement; it determines the initial object symbol corresponding to the target object based on the shape of the target object; by determining the initial object symbol for the target object, it realizes the symbolization of the target object, avoiding shape differences caused by manual drawing, and by symbolizing the target object, it achieves unified management of object drawing; it adjusts the size of the initial object symbol according to the size of the target object to obtain the target symbol of the target object in the target top view; by adjusting the initial object symbol based on the size, it makes the adjusted target symbol match the size of the target object, realizing accurate depiction of the target object based on objective data, ensuring the accuracy of the shape and size of the drawing elements, and realizing the standardization of drawing.
[0050] This embodiment provides a method for rapid, accurate, and standardized accident scene investigation and mapping based on point cloud and image technology on a mobile terminal. It fundamentally transforms the traditional purely manual investigation mode, solving its three core problems of efficiency bottleneck, lack of accuracy, and insufficient standardization. It can quickly complete the drawing of "accident scene map", freeing investigators from heavy manual labor and shortening the entire process time from "hours" to "minutes" from "on-site investigation" to "standard scene map". At the same time, it significantly improves the accuracy and evidentiary value of the scene map.
[0051] In some alternative embodiments, based on the above embodiments, step 102 may include: Point cloud data was collected from the target accident site to obtain high-density point cloud data.
[0052] Optionally, high-density point cloud data can be colorless 3D point clouds or high-density point clouds. When the high-density point cloud data is a colorless 3D point cloud, it can be obtained by point cloud acquisition using LiDAR or depth cameras. However, when the high-density point cloud data is a high-density point cloud, it needs to be combined with a real-world image based on the point cloud. The real-world image can be obtained based on RGB camera acquisition. For example, a Simultaneous Localization and Mapping Device (SLAM device) that integrates multiple sensors (LiDAR + RGB camera, etc.) can be used to simultaneously acquire point clouds and color images to obtain high-density point clouds.
[0053] The three-dimensional high-density point cloud data is mapped onto a two-dimensional top-view plane to obtain a top view of the target.
[0054] Optionally, the process of obtaining the target top view may include: fixing the Z-axis height, determining an XY plane as the top view reference, and mapping the high-density point cloud data onto the XY plane to obtain the target top view.
[0055] like Figure 2 As shown above, in the above Figure 1 Based on the illustrated embodiment, step 106 may include the following steps: Step 1061: Determine the corresponding target symbol set based on the scene type corresponding to the target accident scene.
[0056] Each scene type corresponds to a symbol set, which includes preset object symbols for multiple different objects.
[0057] Different accident scenes correspond to different scenario types. For example, a traffic accident scene corresponds to a traffic scenario, while a public safety accident scene corresponds to a public place (such as a shopping mall or park). The objects involved in the accident differ in different scenarios; therefore, corresponding symbol sets can be established for different scenarios. For example, Figure 3 This is a schematic diagram illustrating the application of a method provided in an exemplary embodiment of this disclosure to a traffic accident scene. For example... Figure 3 As shown in the figure, in this embodiment, the list of legends on the left is the set of target symbols corresponding to the traffic scene, which may include, but is not limited to, the following: trucks, cars, electric vehicles, etc.
[0058] Step 1062: Based on the category and / or shape of the target object, match it with multiple preset object symbols in the target symbol set, and determine the preset object symbol that matches the shape of the target object as the initial object symbol.
[0059] This embodiment can directly determine the corresponding initial object symbol for the target object from the target symbol set by category, for example, such as Figure 3In the example shown, after processing the top view of the target object using a semantic segmentation network model, if a target object is identified as a sedan, a preset object symbol of the category "sedan" is directly selected from the target symbol set as the initial object symbol for that target object. Alternatively, the shape of the target object can be matched with multiple preset object symbols in the target symbol set. Through matching (the matching process can be implemented through similarity calculation, deep neural networks, etc.), the shape of the target object is determined to be closest to that of a sedan, and the preset object symbol corresponding to the sedan is selected as the initial object symbol. Alternatively, both methods can be combined. For example, if the shape recognition shows that the target object is similar in shape to both a truck and a sedan, further matching by category can be performed to determine a more accurate symbol. This embodiment achieves fast and accurate determination of the initial object symbol by combining shape and / or category to determine the corresponding initial object symbol for the target object. Furthermore, by matching from preset object symbols, the initial object symbol obtained is a standard shape, overcoming the non-standard and error problems caused by human drawing.
[0060] Figure 4 This is a schematic flowchart illustrating the method for determining a target symbol provided in an exemplary embodiment of this disclosure. Figure 4 As shown above, in the above Figure 1 Based on the illustrated embodiment, step 108 may include the following steps: Step 1081: According to the position information of at least one target object, insert at least one initial object symbol into the target top view to obtain at least one initial object symbol.
[0061] Optionally, after determining the initial object symbol, in order to accurately represent the target object in the target top view, it is also necessary to determine the position information of the target object so as to achieve accurate insertion of the initial object symbol. Optionally, the position information and orientation of the target object are determined based on the point cloud data corresponding to the target object.
[0062] In this embodiment, the coordinate information corresponding to the point cloud data of the target object can be used to determine the two-dimensional coordinate information projected onto the top view of the target. This two-dimensional coordinate information can be used as the position information. In addition, at the accident scene, the orientation of the object can play a significant role in the judgment of the accident. Therefore, it is also necessary to determine the orientation of the target object. Optionally, the orientation of the target object can be determined based on its shape. For example, if the front and rear of a vehicle have different shapes, the vehicle orientation can be determined based on the shape difference.
[0063] Step 1082: Perform stretching on at least one initial object symbol according to the orientation of at least one target object until the length of the initial object symbol matches the size of the target object, thus obtaining the target symbol.
[0064] In this embodiment, the preset object symbols are typically small in size for ease of display. Therefore, the initial object symbols determined solely based on shape and / or name matching are also usually small in size. To correctly display the target object, the size of the initial object symbols needs to be adjusted. For example... Figure 5 yes Figure 3 This is a schematic diagram illustrating the resizing of an initial object symbol in an exemplary embodiment. Figure 5 As shown, target object "A" is the target symbol after size adjustment, while target object "B" is the initial object symbol during adjustment. Optionally, the size of the initial object symbol can be adjusted along the orientation of the target object, for example, by stretching it along the orientation of the target object until the length and width of the initial object symbol match the length and width of the target object, thus obtaining the desired result. Figure 6 The target symbol of the target object "B" shown is shown. Figure 6 yes Figure 5 The illustrated exemplary embodiment shows a schematic diagram after the initial object symbol has been sized. This embodiment achieves accurate insertion of the initial object symbol through positioning and stretches the initial object symbol according to the orientation of the target object, realizing directional stretching of the initial object symbol. This makes the matching process between the stretched target symbol and the target object size more accurate, avoiding the problem of repeated stretching caused by insufficient or excessive stretching.
[0065] This embodiment realizes intelligent vectorized drawing of symbols based on point cloud base map. It adopts the "one-stroke drawing" method to effectively transform subjective drawing into accurate drawing based on objective data, ensuring the accuracy of the absolute position, shape and size of drawing elements, and realizing the standardization of drawing.
[0066] Figure 7 This is a flowchart illustrating a method for normalizing the drawing of objects at an accident scene, provided in another exemplary embodiment of this disclosure. This embodiment can be applied to electronic devices, such as... Figure 7 As shown, it includes the following steps: Step 102: Determine the target top view based on the high-density point cloud data of the target accident site.
[0067] Step 104: Identify the size of the target object in the top view, as well as the category and / or shape of the target object.
[0068] Step 106: Determine the initial object symbol corresponding to the target object based on the category and / or shape of the target object.
[0069] Step 108: Adjust the size of the initial object symbol according to the size of the target object to obtain the target symbol of the target object in the top view of the target.
[0070] The specific implementation and technical effects of steps 102 to 108 above can be found in [reference needed]. Figure 1 The provided embodiments are for illustrative purposes only and will not be elaborated upon further here.
[0071] Step 110: Adjust the target symbol accordingly based on at least one received adjustment instruction to obtain the adjusted target symbol.
[0072] exist Figure 1 In the illustrated embodiment, the initial drawing of the target object in the target top view is basically completed, achieving a standardized display of the target object's basic shape and size in the target top view. However, the initially drawn object symbol may differ from the actual target object, for example, there may be angular deviations or differences in aspect ratio. To solve the problem of mismatch between the target symbol and the target object, this embodiment uses adjustment commands to make corresponding adjustments to the target symbol, so that the adjusted target symbol matches the target object more accurately, enabling a more accurate description of the target accident scene and providing a basis for staff to handle the accident correctly.
[0073] Figure 8 This is a schematic flowchart illustrating the adjustment of a target symbol in a method provided by another exemplary embodiment of this disclosure. For example... Figure 8 As shown above Figure 7 Based on the illustrated embodiment, step 110 may include the following steps: Step 1101: Receive at least one adjustment instruction and determine at least one corresponding adjustment operation based on the at least one adjustment instruction.
[0074] Among them, at least one adjustment operation includes, but is not limited to, at least one of the following: rotation, translation, scaling, and changing aspect ratio; each adjustment instruction corresponds to one adjustment action.
[0075] Optionally, the adjustment instructions can be user-inputted or determined by a deep learning algorithm, for example, by receiving user-inputted adjustment instructions on a terminal (e.g., a tablet computer, etc.) that displays the top view of the target.
[0076] Step 1102: Perform at least one adjustment operation on the target object symbol in a preset order to obtain the adjusted target symbol.
[0077] Optionally, the preset order can be determined based on the time of receiving the adjustment instruction, or based on the difficulty of the adjustment operation, for example, by arranging complex adjustments later.
[0078] In this embodiment, when at least one adjustment instruction is received, the instructions are received in a specific order. To avoid errors caused by performing multiple adjustment operations simultaneously, at least one adjustment operation can be performed on the target symbol in the order in which the instructions are received. Optionally, a corresponding timestamp can be assigned to each adjustment instruction when it is received. After obtaining the adjustment operation, at least one adjustment operation is sorted according to the timestamp, and the target symbol is adjusted sequentially according to the sorted at least one adjustment action to obtain the adjusted target symbol.
[0079] Any of the object normalization drawing methods for accident scenes provided in this disclosure can be executed by any suitable device with data processing capabilities, including but not limited to: terminal devices and servers. Alternatively, any of the object normalization drawing methods for accident scenes provided in this disclosure can be executed by a processor, such as by a processor executing any of the object normalization drawing methods for accident scenes mentioned in this disclosure by calling corresponding instructions stored in memory. Further details will not be elaborated below.
[0080] Exemplary device Figure 9 This is a schematic diagram of the structure of an object standardization drawing device for accident scenes provided in an exemplary embodiment of this disclosure. Figure 9 As shown, the apparatus provided in this embodiment includes: Data acquisition module 91 is used to determine the target top view based on high-density point cloud data of the target accident site; Target recognition module 92 is used to identify the shape and size of the target object in the top view of the target; Symbol determination module 93 is used to determine the initial object symbol corresponding to the target object based on the shape of the target object; The symbol adjustment module 94 is used to adjust the size of the initial object symbol according to the size of the target object, so as to obtain the target symbol of the target object in the target top view.
[0081] The apparatus provided in the above embodiments of this disclosure determines a target top view based on high-density point cloud data of the target accident scene; it enables rapid and automatic acquisition of the top view of the accident scene, providing a foundation for subsequent drawing of the target object; it identifies the shape and size of the target object in the target top view; automatic identification improves the recognition efficiency of the target object, eliminating the need for manual measurement; it determines the initial object symbol corresponding to the target object based on the shape of the target object; by determining the initial object symbol for the target object, it realizes the symbolization of the target object, avoiding shape differences caused by manual drawing, and by symbolizing the target object, it achieves unified management of object drawing; it adjusts the size of the initial object symbol according to the size of the target object to obtain the target symbol of the target object in the target top view; by adjusting the initial object symbol based on the size, it makes the adjusted target symbol match the size of the target object, realizing accurate depiction of the target object based on objective data, ensuring the accuracy of the shape and size of the drawing elements, and realizing the standardization of drawing.
[0082] In some alternative embodiments, the apparatus provided in this embodiment may further include: The instruction adjustment module is used to adjust the target symbol according to at least one received adjustment instruction to obtain the adjusted target symbol.
[0083] Optionally, the instruction adjustment module is specifically used to receive at least one adjustment instruction, determine at least one corresponding adjustment operation based on the at least one adjustment instruction; the at least one adjustment operation includes at least one of the following: rotation, translation, scaling, and changing aspect ratio; and perform at least one adjustment operation on the target object symbol in a preset order to obtain the adjusted target symbol.
[0084] In some alternative embodiments, the apparatus provided in this embodiment may further include: The position and orientation module is used to determine the position and orientation of the target object based on the point cloud data corresponding to the target object.
[0085] Optionally, the symbol adjustment module is specifically used to insert at least one initial object symbol into the target top view according to the position information of at least one target object to obtain at least one initial object symbol; and to perform stretching processing on at least one initial object symbol according to the orientation of at least one target object until the length of the initial object symbol matches the size of the target object to obtain the target symbol.
[0086] In some optional embodiments, the symbol determination module 93 is specifically used to determine the corresponding target symbol set according to the scene type corresponding to the target accident scene; each scene type corresponds to a symbol set, and the symbol set includes multiple preset object symbols of different objects; based on the category and / or shape of the target object and the multiple preset object symbols in the target symbol set, the preset object symbol that matches the shape of the target object is determined as the initial object symbol.
[0087] In some optional embodiments, the data acquisition module 91 is specifically used to collect point cloud data of the target accident site to obtain high-density point cloud data; and to map the three-dimensional high-density point cloud data onto a two-dimensional top view plane to obtain a top view of the target.
[0088] The exemplary embodiment of the accident scene object standardization drawing device provided in this disclosure corresponds to the above-described exemplary accident scene object standardization drawing method in terms of implementation. The corresponding content of the two can be referenced, combined, and cited from each other, and will not be repeated here. The beneficial technical effects corresponding to the exemplary embodiment of the accident scene object standardization drawing device provided in this disclosure can be found in the corresponding beneficial technical effects of the above-described exemplary accident scene object standardization drawing method, and will not be repeated here.
[0089] Exemplary electronic devices Below, for reference Figure 10 This describes an electronic device according to embodiments of the present disclosure. The electronic device may be either or both of a first device and a second device, or a standalone device independent of them, which may communicate with the first device and the second device to receive acquired input signals from them.
[0090] Figure 10 A block diagram of an electronic device according to an embodiment of the present disclosure is shown.
[0091] like Figure 10 As shown, the electronic device includes one or more processors and memory.
[0092] A processor can be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and can control other components in an electronic device to perform desired functions.
[0093] The memory can store one or more computer program products, and the memory can include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program products can be stored on the computer-readable storage medium, and the processor can run the computer program products to implement the object normalization drawing method for accident scenes according to the various embodiments of this disclosure described above, and / or other desired functions.
[0094] In one example, the electronic device may also include input devices and output devices, which are interconnected via a bus system and / or other forms of connection mechanism (not shown).
[0095] In addition, the input device may also include, for example, a keyboard, a mouse, etc.
[0096] This output device can output various information to the outside, including determined distance information, direction information, etc. The output device may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.
[0097] Of course, for the sake of simplicity, Figure 10 Only some of the components of the electronic device relevant to this disclosure are shown, omitting components such as buses, input / output interfaces, etc. In addition, the electronic device may include any other suitable components depending on the specific application.
[0098] In addition to the methods and devices described above, embodiments of this disclosure may also be computer program products comprising computer program instructions that, when executed by a processor, cause the processor to perform the steps in the object normalization drawing method for accident scenes according to various embodiments of this disclosure as described in the foregoing portion of this specification.
[0099] The computer program product can be written in any combination of one or more programming languages to perform the operations of the embodiments of this disclosure. The programming languages include object-oriented programming languages such as Java and C++, as well as conventional procedural programming languages such as C or similar languages. The program code can be executed entirely on a user's computing device, partially on a user's computing device, as a standalone software package, partially on a user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.
[0100] Furthermore, embodiments of this disclosure may also be computer-readable storage media storing computer program instructions that, when executed by a processor, cause the processor to perform the steps in the object normalization drawing method for accident scenes according to various embodiments of this disclosure as described in the foregoing portion of this specification.
[0101] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.
[0102] The basic principles of this disclosure have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this disclosure are merely examples and not limitations, and should not be considered as essential features of each embodiment of this disclosure. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the scope of this disclosure to the necessity of employing the aforementioned specific details for implementation.
[0103] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For system embodiments, since they largely correspond to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.
[0104] The block diagrams of devices, apparatuses, devices, and systems disclosed herein are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.
[0105] The methods and apparatus of this disclosure may be implemented in many ways. For example, they may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the methods is for illustrative purposes only, and the steps of the methods of this disclosure are not limited to the order specifically described above unless otherwise specifically stated. Furthermore, in some embodiments, this disclosure may also be implemented as a program recorded on a recording medium, the program including machine-readable instructions for implementing the methods according to this disclosure. Thus, this disclosure also covers recording media storing programs for performing the methods according to this disclosure.
[0106] It should also be noted that in the apparatus, devices, and methods of this disclosure, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered as equivalent solutions to this disclosure.
[0107] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of this disclosure. Therefore, this disclosure is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features disclosed herein.
[0108] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of this disclosure to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations therein.
Claims
1. A method for standardized drawing of objects at an accident scene, characterized in that, include: Based on high-density point cloud data of the target accident site, a top-down view of the target is determined; Identify the size of the target object in the top view of the target, as well as the category and / or shape of the target object; Determine the initial object symbol corresponding to the target object based on the category and / or shape of the target object; The size of the initial object symbol is adjusted according to the size of the target object to obtain the target symbol of the target object in the target top view.
2. The method according to claim 1, characterized in that, Also includes: The target symbol is adjusted accordingly based on at least one received adjustment instruction to obtain the adjusted target symbol.
3. The method according to claim 2, characterized in that, The step of adjusting the target symbol according to at least one received adjustment instruction to obtain the adjusted target symbol includes: Receive the at least one adjustment instruction, and determine at least one corresponding adjustment operation based on the at least one adjustment instruction; the at least one adjustment operation includes at least one of the following: rotation, translation, scaling, and changing aspect ratio; At least one adjustment operation is performed on the target object symbol in a preset order to obtain the adjusted target symbol.
4. The method according to any one of claims 1-3, characterized in that, After determining the target top view based on the high-density point cloud of the target accident site, the process also includes: Based on the point cloud data corresponding to the target object, determine the location information and orientation of the target object.
5. The method according to claim 4, characterized in that, The step of adjusting the size of the initial object symbol according to the size of the target object to obtain the target symbol corresponding to the target object includes: According to the location information of the at least one target object, the at least one initial object symbol is inserted into the top view of the target to obtain at least one initial object symbol; The at least one initial object symbol is stretched according to the orientation of the at least one target object until the length of the initial object symbol matches the size of the target object, thus obtaining the target symbol.
6. The method according to any one of claims 1-5, characterized in that, The step of determining the initial object symbol corresponding to the target object based on the category and / or shape of the target object includes: Based on the scene type corresponding to the target accident scene, a corresponding target symbol set is determined; each scene type corresponds to a symbol set, and the symbol set includes multiple preset object symbols of different objects; Based on the category and / or shape of the target object, multiple preset object symbols in the target symbol set are matched to determine the preset object symbol that matches the shape of the target object as the initial object symbol.
7. The method according to any one of claims 1-6, characterized in that, The determination of the target top view based on high-density point cloud data of the target accident site includes: Point cloud data is collected from the target accident site to obtain the high-density point cloud data; The three-dimensional high-density point cloud data is mapped onto a two-dimensional top-view plane to obtain the target top view.
8. A device for standardizing the drawing of objects at an accident scene, characterized in that, include: The data acquisition module is used to determine the top view of the target based on high-density point cloud data of the target accident site; The target recognition module is used to identify the shape and size of the target object in the top view of the target; A symbol determination module is used to determine the initial object symbol corresponding to the target object based on the shape of the target object; The symbol adjustment module is used to adjust the size of the initial object symbol according to the size of the target object, so as to obtain the target symbol of the target object in the target top view.
9. An electronic device, characterized in that, include: Memory, used to store computer program products; A processor is configured to execute a computer program product stored in the memory, wherein when the computer program product is executed, it implements the object standardization drawing method for accident scenes as described in any one of claims 1-7.
10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the object normalization drawing method for accident scenes as described in any one of claims 1-7.