Garbage throwing automatic detection method and system based on target tracking

Abstract

The invention discloses an automatic garbage throwing detection method and system based on target tracking, and the method comprises the steps: recognizing the layout of throwing equipment from an image of a throwing region, and calibrating a plurality of throwing space regions in the throwing region according to the layout of the throwing equipment, so as to form a throwing strategy matched with the plurality of throwing space regions; a garbage throwing dynamic image is obtained, framing recognition is conducted on the garbage throwing dynamic image, and throwing attribute information during throwing is obtained; according to the delivery attribute information and the delivery strategy, calibrating the occurrence state of a delivery abnormal event; and according to the occurrence state of the throwing abnormal event and the garbage existence state of the throwing space area, whether current garbage throwing continues to be executed or not is judged. The throwing strategy of each throwing space area is set, throwing abnormities are calibrated in combination with the garbage throwing dynamic attributes in the throwing period, the garbage throwing situation is dynamically recognized, and the detection accuracy and reliability are improved.

Description

Technical Field

[0001] This invention relates to the field of visual recognition technology, and in particular to an automatic detection method and system for waste disposal based on target tracking. Background Technology

[0002] Urban waste management typically relies on manual inspections or rule-based video monitoring, with video monitoring focusing on single frames of waste or bins. While deep learning-based object detection (such as the YOLO model) or object detection algorithms (such as the SORT model) have been employed to analyze waste disposal behavior, the analysis remains limited to detecting whether waste is on the ground. It fails to provide temporal analysis of the entire waste disposal process, cannot comprehensively analyze waste disposal status at both spatial and temporal levels, cannot effectively suppress false detections from single-frame detection, and is easily affected by external factors unrelated to waste disposal, thus reducing detection accuracy and reliability. Summary of the Invention

[0003] Considering that existing waste disposal detection methods typically identify a single target state using a single-frame detection approach, they do not perform temporal identification of the entire waste disposal process and are easily affected by other irrelevant external factors, reducing detection accuracy and reliability. In view of the above problems, this invention is proposed to provide an automatic waste disposal detection method based on target tracking that overcomes or at least partially solves the above problems, comprising:

[0004] The layout of the delivery equipment is identified from the image of the delivery area. Based on the layout of the delivery equipment, several delivery space areas within the delivery area are marked, thereby forming a delivery strategy that matches the several delivery space areas.

[0005] Acquire dynamic images of waste disposal, perform frame-by-frame recognition on the dynamic images of waste disposal to obtain disposal attribute information during the disposal period; and mark the occurrence status of abnormal disposal events based on the disposal attribute information and the disposal strategy.

[0006] Based on the occurrence status of the abnormal disposal event and the state of the garbage in the disposal space area, determine whether to continue the current garbage disposal.

[0007] Optionally, the layout of the delivery equipment is identified from the image of the delivery area, and several delivery space regions within the delivery area are marked according to the layout of the delivery equipment, thereby forming a delivery strategy that matches the several delivery space regions, including:

[0008] Multidimensional feature recognition is performed on the image of the disposal area to obtain the object outline features and object color features of the disposal area; the layout of the disposal equipment is determined based on the object outline features and object color features; wherein the layout of the disposal equipment includes the type, location and structure of all waste containers in the disposal area;

[0009] Based on the location and structure of all waste containers, several disposal space areas are marked to correspond one-to-one with all waste containers in the disposal area; wherein the disposal space area corresponds to the spatial range in which the waste container receives waste.

[0010] Based on the categories of all waste containers, several disposal space areas are distinguished to form a disposal strategy that matches the disposal space areas; wherein the disposal strategy includes the types of waste allowed to be disposed of in each disposal space area and the disposal operation space range.

[0011] Optionally, acquire dynamic images of waste disposal, perform frame-by-frame recognition on the dynamic images of waste disposal to obtain disposal attribute information during the disposal period; based on the disposal attribute information and the disposal strategy, mark the occurrence status of abnormal disposal events, including:

[0012] A three-dimensional dynamic image of waste disposal is acquired, and the three-dimensional dynamic image of waste disposal is processed into frames to obtain several three-dimensional image frames; the several three-dimensional image frames are identified according to the frame sequence to obtain the disposal attribute information of each time stage during the disposal period; wherein the disposal attribute information includes waste type information and waste movement trajectory information.

[0013] Based on the disposal attribute information and the disposal strategy, the occurrence status of disposal anomalies for each waste container within the disposal area is determined; wherein the occurrence status of disposal anomalies includes the occurrence process of waste type incorrect disposal events and / or waste out-of-bounds disposal events.

[0014] Optionally, based on the occurrence status of the abnormal disposal event and the state of the garbage in the disposal space area, it is determined whether to continue the current garbage disposal, including:

[0015] The quantity and type of waste disposed of in each of the several disposal space areas corresponding to all waste containers in the disposal area are obtained, and this is used as the existence status of the disposal space area.

[0016] Based on the occurrence status of the abnormal disposal event and the state of the garbage in the disposal space area, determine whether to continue the current garbage disposal for the corresponding garbage container and change the garbage disposal action status.

[0017] As one aspect of the present invention, embodiments of the present invention also provide an automatic waste disposal detection system based on target tracking, comprising:

[0018] The equipment layout recognition module is used to recognize the layout of the delivery equipment from the image of the delivery area;

[0019] The delivery strategy determination module is used to mark several delivery space areas within the delivery area based on the layout of the delivery equipment, thereby forming a delivery strategy that matches the several delivery space areas.

[0020] The waste disposal attribute determination module is used to acquire dynamic images of waste disposal, perform frame-by-frame recognition on the dynamic images of waste disposal, and obtain waste disposal attribute information during the disposal period.

[0021] The delivery anomaly identification module is used to identify the occurrence status of delivery anomaly events based on delivery attribute information and the delivery strategy.

[0022] The waste disposal processing module is used to determine whether to continue the current waste disposal based on the occurrence status of the disposal anomaly event and the state of waste in the disposal space area.

[0023] Optionally, the device layout recognition module is used to recognize the layout of the delivery device from the delivery area image, including:

[0024] Multidimensional feature recognition is performed on the image of the disposal area to obtain the object outline features and object color features of the disposal area; the layout of the disposal equipment is determined based on the object outline features and object color features; wherein the layout of the disposal equipment includes the type, location and structure of all waste containers in the disposal area;

[0025] The delivery strategy determination module is used to mark several delivery space areas within the delivery area based on the layout of the delivery equipment, thereby forming a delivery strategy that matches the several delivery space areas, including:

[0026] Based on the location and structure of all waste containers, several disposal space areas are marked to correspond one-to-one with all waste containers in the disposal area; wherein the disposal space area corresponds to the spatial range in which the waste container receives waste.

[0027] Based on the categories of all waste containers, several disposal space areas are distinguished to form a disposal strategy that matches the disposal space areas; wherein the disposal strategy includes the types of waste allowed to be disposed of in each disposal space area and the disposal operation space range.

[0028] Optionally, the waste disposal attribute determination module is used to acquire dynamic images of waste disposal, and to perform frame-by-frame recognition of the dynamic images of waste disposal to obtain disposal attribute information during the disposal period, including:

[0029] A three-dimensional dynamic image of waste disposal is acquired, and the three-dimensional dynamic image of waste disposal is processed into frames to obtain several three-dimensional image frames; the several three-dimensional image frames are identified according to the frame sequence to obtain the disposal attribute information of each time stage during the disposal period; wherein the disposal attribute information includes waste type information and waste movement trajectory information.

[0030] The delivery anomaly identification module is used to identify the occurrence status of delivery anomaly events based on delivery attribute information and the delivery strategy, including:

[0031] Based on the disposal attribute information and the disposal strategy, the occurrence status of disposal anomalies for each waste container within the disposal area is determined; wherein the occurrence status of disposal anomalies includes the occurrence process of waste type incorrect disposal events and / or waste out-of-bounds disposal events.

[0032] Optionally, the waste disposal processing module is used to determine whether to continue the current waste disposal based on the occurrence status of the disposal anomaly event and the state of waste presence in the disposal space area, including:

[0033] The quantity and type of waste disposed of in each of the several disposal space areas corresponding to all waste containers in the disposal area are obtained, and this is used as the existence status of the disposal space area.

[0034] Based on the occurrence status of the abnormal disposal event and the state of the garbage in the disposal space area, determine whether to continue the current garbage disposal for the corresponding garbage container and change the garbage disposal action status.

[0035] The beneficial effects of the above-mentioned technical solutions provided in the embodiments of the present invention include at least the following:

[0036] This invention provides an automatic waste disposal detection method and system based on target tracking. The method begins by identifying the layout of waste disposal equipment from images of the disposal area. Based on this layout, several disposal space regions within the disposal area are identified, forming a disposal strategy that matches these regions. Dynamic images of waste disposal are acquired, and these images are segmented and analyzed to obtain disposal attribute information during the disposal period. Based on the disposal attribute information and the disposal strategy, the occurrence status of abnormal disposal events is identified. Finally, based on the occurrence status of abnormal disposal events and the state of waste in the disposal space regions, it is determined whether to continue the current waste disposal process. By setting a disposal strategy for each disposal space region and combining this with the dynamic attributes of waste disposal during the disposal period to identify disposal anomalies, dynamic identification of waste disposal conditions is achieved, improving detection accuracy and reliability.

[0037] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0038] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0039] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0040] Figure 1 This is a flowchart illustrating the automatic detection method for waste disposal based on target tracking provided in an embodiment of the present invention.

[0041] Figure 2 This is a schematic diagram of the automatic waste disposal detection system based on target tracking provided in an embodiment of the present invention. Detailed Implementation

[0042] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0043] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," "outer," "far," "near," "front," and "rear," etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the accompanying drawings and are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0044] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0045] Please see Figure 1 As shown, an embodiment of this application provides an automatic waste disposal detection method based on target tracking. This automatic waste disposal detection method based on target tracking includes:

[0046] The layout of the delivery equipment is identified from the image of the delivery area. Based on the layout of the delivery equipment, several delivery space areas within the delivery area are marked, thereby forming a delivery strategy that matches several delivery space areas.

[0047] Acquire dynamic images of waste disposal, perform frame-by-frame recognition on the dynamic images of waste disposal to obtain disposal attribute information during the disposal period; based on the disposal attribute information and disposal strategy, mark the occurrence status of abnormal disposal events;

[0048] Based on the occurrence of the abnormal disposal event and the state of the garbage in the disposal area, determine whether to continue the current garbage disposal process.

[0049] The beneficial effects of the above embodiments are that the target tracking-based automatic waste disposal detection method sets a disposal strategy for each disposal space area, combines the dynamic attributes of waste disposal during the disposal period to identify disposal anomalies, realizes dynamic identification of waste disposal, and improves detection accuracy and reliability.

[0050] In another embodiment, the layout of the delivery equipment is identified from the image of the delivery area. Based on the layout of the delivery equipment, several delivery space areas within the delivery area are marked, thereby forming a delivery strategy that matches the several delivery space areas, including:

[0051] Multidimensional feature recognition is performed on the image of the disposal area to obtain the object outline features and object color features in the disposal area; based on the object outline features and object color features, the layout of the disposal equipment is determined; the layout of the disposal equipment includes the type, location and structure of all waste containers in the disposal area;

[0052] Based on the location and structure of all waste containers, mark several disposal space areas corresponding to each waste container in the disposal area; where the disposal space area corresponds to the space range in which the waste container receives waste.

[0053] Based on the categories of all waste containers, several disposal areas are distinguished to form a disposal strategy that matches the disposal areas; the disposal strategy includes the types of waste that can be disposed of in each disposal area and the scope of disposal operation space.

[0054] The beneficial effects of the above embodiments are that garbage stations and other disposal areas are typically equipped with multiple garbage bins (i.e., garbage containers), each designed for different types of garbage. To ensure proper garbage sorting in the disposal area, it is necessary to clearly define the layout of all garbage bins and the disposal space area for each bin. This disposal space area can be, but is not limited to, the internal space of each garbage bin and a corresponding portion of the external space above its opening. It is understood that garbage can only be accurately disposed of inside the bin when it is disposed of within the designated disposal space area; otherwise, it will not be disposed of properly and may be disposed of in other bins or directly on the ground. The layout of the disposal equipment and the disposal space areas of all garbage containers directly determine the garbage disposal strategy for the disposal area. Only by adhering to this strategy can the correct and proper disposal of garbage be guaranteed.

[0055] In practice, panoramic images of the disposal area are acquired, and multi-dimensional feature recognition of image contours and colors is performed on these images to obtain the contour and color features of all objects within the disposal area. These objects primarily include all trash cans within the disposal area. Based on these contour and color features, the category (e.g., the type of waste the can is intended to hold), location, and structure (e.g., the shape and size of the can) of each trash can are determined. Then, based on the location and structure of all trash cans, the corresponding waste-receiving space for each can is marked. This space includes the internal space of each trash can and a portion of the external space above its opening. Only by aligning the trash can with this space can incorrect waste disposal be avoided. Furthermore, based on the category of all trash cans, the disposal strategy for each disposal space area is differentiated according to the type of waste intended to be placed in each can. This clarifies the types of waste allowed to be disposed of and the disposal operation space range for each trash can's disposal space area, providing a basis for subsequent accurate waste disposal.

[0056] In another embodiment, dynamic images of waste disposal are acquired, and the images are segmented and identified to obtain disposal attribute information during the disposal period. Based on the disposal attribute information and the disposal strategy, the occurrence status of abnormal disposal events is marked, including:

[0057] A three-dimensional dynamic image of waste disposal is acquired, and the image is processed into frames to obtain several three-dimensional image frames. The frames are then identified according to their temporal sequence to obtain the disposal attribute information for each time stage during the disposal period. The disposal attribute information includes information on the type of waste disposed of and the trajectory of the disposed waste.

[0058] Based on the disposal attribute information and disposal strategy, the occurrence status of disposal anomalies for each waste container within the disposal area is marked; the occurrence status of disposal anomalies includes the occurrence process of waste type mis-disposal events and / or waste out-of-bounds disposal events.

[0059] The beneficial effect of the above embodiments is that garbage disposal in the disposal area ensures that the collected garbage is accurately placed into all garbage bins according to their types. In actual operation, garbage disposal may result in incorrect garbage type disposal and / or garbage not being accurately placed into the garbage bins. To perform temporal-domain recognition of the entire garbage disposal process, a three-dimensional dynamic image of garbage disposal is first acquired, and the above three-dimensional dynamic image is processed into frames to obtain a sequence containing several three-dimensional image frames. It can be understood that each three-dimensional image frame in the above sequence corresponds to the garbage state at a corresponding moment in the garbage disposal process (such as the spatial action / shape of garbage disposal, the type of garbage disposed of, etc.). By framing the three-dimensional dynamic image of garbage disposal, a reliable data foundation can be provided for the identification of disposal attributes at each time point in the entire disposal process. Specifically, all three-dimensional image frames are identified according to the frame processing sequence to obtain the garbage type information and garbage movement trajectory information for each time stage (i.e., all time points) during the disposal period, effectively representing both the garbage type itself and the garbage disposal action. Furthermore, based on the aforementioned waste disposal attribute information and disposal strategy, the occurrence process of waste type mis-disposal events and / or waste out-of-bounds disposal events is marked, providing a basis for subsequent adjustments to waste disposal status.

[0060] In another embodiment, determining whether to continue the current waste disposal based on the occurrence status of the disposal anomaly event and the state of waste in the disposal space area includes:

[0061] Obtain the quantity and type of waste already disposed of in each of the several disposal space areas corresponding to all waste containers in the disposal area, and use this as the existence status of the disposal space area;

[0062] Based on the occurrence status of the abnormal disposal event and the state of the garbage in the disposal space area, determine whether to continue the current garbage disposal for the corresponding garbage container and change the garbage disposal action status.

[0063] The beneficial effects of the above embodiments are as follows: In actual operation, the quantity and type of garbage disposed of in each of the several disposal space areas corresponding to all garbage containers in the disposal area are obtained. Then, based on the occurrence status of the disposal anomaly event and the garbage existence status in the disposal space area, it is determined whether the disposal anomaly event is in the initial stage or whether the quantity and type of garbage disposed of in the disposal space area meet the pre-quantity range and type conditions. If so, the current garbage disposal is continued for the corresponding garbage container; otherwise, the current garbage disposal is stopped for the corresponding garbage container, and the garbage container corresponding to the garbage disposal action is changed to ensure the efficiency and reliability of garbage disposal.

[0064] Please see Figure 2 As shown, an embodiment of this application provides an automatic waste disposal detection system based on target tracking. This automatic waste disposal detection system based on target tracking includes:

[0065] The equipment layout recognition module is used to recognize the layout of the delivery equipment from the image of the delivery area;

[0066] The deployment strategy determination module is used to mark several deployment space areas within the deployment area based on the deployment equipment layout, thereby forming a deployment strategy that matches several deployment space areas.

[0067] The waste disposal attribute determination module is used to acquire dynamic images of waste disposal, perform frame-by-frame recognition on the dynamic images of waste disposal, and obtain disposal attribute information during the disposal period.

[0068] The delivery anomaly identification module is used to identify the occurrence status of delivery anomaly events based on delivery attribute information and delivery strategy;

[0069] The waste disposal module is used to determine whether to continue the current waste disposal process based on the occurrence status of abnormal disposal events and the state of waste in the disposal space area.

[0070] The beneficial effects of the above embodiments are that the target tracking-based automatic waste disposal detection system, by setting a disposal strategy for each disposal space area and combining the dynamic attributes of waste disposal during the disposal period to identify disposal anomalies, achieves dynamic identification of waste disposal conditions, thereby improving detection accuracy and reliability.

[0071] In another embodiment, the device layout recognition module is used to recognize the layout of the delivery device from the delivery area image, including:

[0072] Multidimensional feature recognition is performed on the image of the disposal area to obtain the object outline features and object color features in the disposal area; based on the object outline features and object color features, the layout of the disposal equipment is determined; the layout of the disposal equipment includes the type, location and structure of all waste containers in the disposal area;

[0073] The deployment strategy determination module is used to mark several deployment space areas within the deployment zone based on the deployment equipment layout, thereby forming a deployment strategy that matches several deployment space areas, including:

[0074] Based on the location and structure of all waste containers, mark several disposal space areas corresponding to each waste container in the disposal area; where the disposal space area corresponds to the space range in which the waste container receives waste.

[0075] Based on the categories of all waste containers, several disposal areas are distinguished to form a disposal strategy that matches the disposal areas; the disposal strategy includes the types of waste that can be disposed of in each disposal area and the scope of disposal operation space.

[0076] In another embodiment, the waste disposal attribute determination module is used to acquire dynamic images of waste disposal, perform frame-by-frame recognition of the dynamic images of waste disposal, and obtain waste disposal attribute information during the disposal period, including:

[0077] A three-dimensional dynamic image of waste disposal is acquired, and the image is processed into frames to obtain several three-dimensional image frames. The frames are then identified according to their temporal sequence to obtain the disposal attribute information for each time stage during the disposal period. The disposal attribute information includes information on the type of waste disposed of and the trajectory of the disposed waste.

[0078] The delivery anomaly identification module is used to identify the occurrence status of delivery anomaly events based on delivery attribute information and delivery strategies, including:

[0079] Based on the disposal attribute information and disposal strategy, the occurrence status of disposal anomalies for each waste container within the disposal area is marked; the occurrence status of disposal anomalies includes the occurrence process of waste type mis-disposal events and / or waste out-of-bounds disposal events.

[0080] In another embodiment, the waste disposal processing module is used to determine whether to continue the current waste disposal based on the occurrence status of the disposal anomaly event and the state of waste in the disposal space area, including:

[0081] Obtain the quantity and type of waste already disposed of in each of the several disposal space areas corresponding to all waste containers in the disposal area, and use this as the existence status of the disposal space area;

[0082] Based on the occurrence status of the abnormal disposal event and the state of the garbage in the disposal space area, determine whether to continue the current garbage disposal for the corresponding garbage container and change the garbage disposal action status.

[0083] The automatic waste disposal detection system based on target tracking of the present invention operates and has the same effect as the aforementioned automatic waste disposal detection method based on target tracking, and will not be described again here.

[0084] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. This disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims. Thus, if these modifications and variations of the invention fall within the scope of the claims of the invention and their equivalents, the invention is also intended to include these modifications and variations.

Claims

1. An automatic detection method for waste disposal based on target tracking, characterized in that, include: The layout of the delivery equipment is identified from the image of the delivery area. Based on the layout of the delivery equipment, several delivery space areas within the delivery area are marked, thereby forming a delivery strategy that matches the several delivery space areas. Acquire dynamic images of waste disposal, perform frame-by-frame recognition on the dynamic images of waste disposal to obtain disposal attribute information during the disposal period; and mark the occurrence status of abnormal disposal events based on the disposal attribute information and the disposal strategy. Based on the occurrence status of the abnormal disposal event and the state of the garbage in the disposal space area, determine whether to continue the current garbage disposal.

2. The automatic detection method for waste disposal based on target tracking as described in claim 1, characterized in that: The layout of the delivery equipment is identified from the image of the delivery area. Based on the layout of the delivery equipment, several delivery space areas within the delivery area are marked, thereby forming a delivery strategy that matches the several delivery space areas, including: Multidimensional feature recognition is performed on the image of the disposal area to obtain the object outline features and object color features of the disposal area; the layout of the disposal equipment is determined based on the object outline features and object color features; wherein the layout of the disposal equipment includes the type, location and structure of all waste containers in the disposal area; Based on the location and structure of all waste containers, several disposal space areas are marked to correspond one-to-one with all waste containers in the disposal area; wherein the disposal space area corresponds to the spatial range in which the waste container receives waste. Based on the categories of all waste containers, several disposal space areas are distinguished to form a disposal strategy that matches the disposal space areas; wherein the disposal strategy includes the types of waste allowed to be disposed of in each disposal space area and the disposal operation space range.

3. The automatic detection method for waste disposal based on target tracking as described in claim 1, characterized in that: Acquire dynamic images of garbage disposal, perform frame-by-frame recognition on the dynamic images of garbage disposal, and obtain disposal attribute information during the disposal period; Based on the delivery attribute information and the delivery strategy, the occurrence status of delivery anomalies is identified, including: A three-dimensional dynamic image of garbage disposal is acquired, and the three-dimensional dynamic image of garbage disposal is processed into frames to obtain a number of three-dimensional image frames. The plurality of three-dimensional image frames are identified according to the frame-by-frame time sequence to obtain the respective disposal attribute information for each time stage during the disposal period; wherein the disposal attribute information includes information on the type of waste disposed of and information on the movement trajectory of the waste disposed of. Based on the disposal attribute information and the disposal strategy, the occurrence status of disposal anomalies for each waste container within the disposal area is determined; wherein the occurrence status of disposal anomalies includes the occurrence process of waste type incorrect disposal events and / or waste out-of-bounds disposal events.

4. The automatic detection method for waste disposal based on target tracking as described in claim 1, characterized in that: Based on the occurrence status of the abnormal disposal event and the state of the garbage in the disposal space area, determine whether to continue the current garbage disposal, including: The quantity and type of waste disposed of in each of the several disposal space areas corresponding to all waste containers in the disposal area are obtained, and this is used as the existence status of the disposal space area. Based on the occurrence status of the abnormal disposal event and the state of the garbage in the disposal space area, determine whether to continue the current garbage disposal for the corresponding garbage container and change the garbage disposal action status.

5. An automatic waste disposal detection system based on target tracking, characterized in that, include: The equipment layout recognition module is used to recognize the layout of the delivery equipment from the image of the delivery area; The delivery strategy determination module is used to mark several delivery space areas within the delivery area based on the layout of the delivery equipment, thereby forming a delivery strategy that matches the several delivery space areas. The waste disposal attribute determination module is used to acquire dynamic images of waste disposal, perform frame-by-frame recognition on the dynamic images of waste disposal, and obtain waste disposal attribute information during the disposal period. The delivery anomaly identification module is used to identify the occurrence status of delivery anomaly events based on delivery attribute information and the delivery strategy. The waste disposal processing module is used to determine whether to continue the current waste disposal based on the occurrence status of the disposal anomaly event and the state of waste in the disposal space area.

6. The automatic waste disposal detection system based on target tracking as described in claim 5, characterized in that: The device layout recognition module is used to recognize the layout of the delivery device from the delivery area image, including: Multidimensional feature recognition is performed on the image of the disposal area to obtain the object outline features and object color features of the disposal area; the layout of the disposal equipment is determined based on the object outline features and object color features; wherein the layout of the disposal equipment includes the type, location and structure of all waste containers in the disposal area; The delivery strategy determination module is used to mark several delivery space areas within the delivery area based on the layout of the delivery equipment, thereby forming a delivery strategy that matches the several delivery space areas, including: Based on the location and structure of all waste containers, several disposal space areas are marked to correspond one-to-one with all waste containers in the disposal area; wherein the disposal space area corresponds to the spatial range in which the waste container receives waste. Based on the categories of all waste containers, several disposal space areas are distinguished to form a disposal strategy that matches the disposal space areas; wherein the disposal strategy includes the types of waste allowed to be disposed of in each disposal space area and the disposal operation space range.

7. The automatic waste disposal detection system based on target tracking as described in claim 5, characterized in that: The waste disposal attribute determination module is used to acquire dynamic images of waste disposal, and to perform frame-by-frame recognition of the dynamic images of waste disposal to obtain disposal attribute information during the disposal period, including: A three-dimensional dynamic image of waste disposal is acquired, and the three-dimensional dynamic image of waste disposal is processed into frames to obtain several three-dimensional image frames; the several three-dimensional image frames are identified according to the frame sequence to obtain the disposal attribute information of each time stage during the disposal period; wherein the disposal attribute information includes waste type information and waste movement trajectory information. The delivery anomaly identification module is used to identify the occurrence status of delivery anomaly events based on delivery attribute information and the delivery strategy, including: Based on the disposal attribute information and the disposal strategy, the occurrence status of disposal anomalies for each waste container within the disposal area is determined; wherein the occurrence status of disposal anomalies includes the occurrence process of waste type incorrect disposal events and / or waste out-of-bounds disposal events.

8. The automatic waste disposal detection system based on target tracking as described in claim 5, characterized in that: The waste disposal processing module is used to determine whether to continue the current waste disposal based on the occurrence status of the disposal anomaly event and the state of waste in the disposal space area, including: The quantity and type of waste disposed of in each of the several disposal space areas corresponding to all waste containers in the disposal area are obtained, and this is used as the existence status of the disposal space area. Based on the occurrence status of the abnormal disposal event and the state of the garbage in the disposal space area, determine whether to continue the current garbage disposal for the corresponding garbage container and change the garbage disposal action status.

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