CN112347810A - Method and device for detecting moving target object and storage medium - Google Patents
Method and device for detecting moving target object and storage medium Download PDFInfo
- Publication number
- CN112347810A CN112347810A CN201910725138.0A CN201910725138A CN112347810A CN 112347810 A CN112347810 A CN 112347810A CN 201910725138 A CN201910725138 A CN 201910725138A CN 112347810 A CN112347810 A CN 112347810A
- Authority
- CN
- China
- Prior art keywords
- target object
- moving
- frames
- frame
- images
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 45
- 238000001514 detection method Methods 0.000 claims abstract description 48
- 238000004590 computer program Methods 0.000 claims description 10
- 238000012163 sequencing technique Methods 0.000 claims description 9
- 238000010586 diagram Methods 0.000 description 10
- 238000012544 monitoring process Methods 0.000 description 9
- 230000008569 process Effects 0.000 description 7
- 230000006870 function Effects 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000001629 suppression Effects 0.000 description 2
- 206010063385 Intellectualisation Diseases 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000007123 defense Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/48—Matching video sequences
Abstract
The invention provides a method and a device for detecting a moving target object and a storage medium. The method comprises the following steps: acquiring multi-frame images, performing target object matching on the multi-frame images, determining the number of continuous moving frames in which the moving distance of the same target object in the multi-frame images in two adjacent frames of images meets a preset distance range, and determining the same target object as a moving target object if the number of the continuous moving frames is larger than or equal to a preset threshold value. The method introduces the moving distance of the same target object, counts the number of moving frames of the same target object moving continuously in the multi-frame images according to the moving distance, greatly reduces the false alarm rate of the moving target object, and improves the accuracy rate of moving detection.
Description
Technical Field
The embodiment of the invention relates to the technical field of motion detection, in particular to a method and a device for detecting a moving target object and a storage medium.
Background
With the increasing requirements of people on security and protection, the video monitoring technology is developing towards digitization, networking and intellectualization, and has wide application prospects in residential communities, business districts, national defense fields and the like. The mobile detection technology is added into the intelligent monitoring system, so that the target detection can be automatically carried out on the video image, and the performance of the monitoring system is greatly improved. The motion detection technology is a basis for judging whether a monitoring scene has a foreign object or not, and is a condition for triggering the behavior of the alarm device. Once an abnormal condition occurs, an alarm is sent immediately to remind monitoring personnel, a video recording function is started simultaneously, and abnormal sites are recorded and stored, so that manpower is saved, and a large amount of storage space is saved.
The existing mobile detection method has the disadvantages of high resource consumption, high memory requirement and high-performance CPU support, low detection accuracy and high possibility of false alarm.
Disclosure of Invention
The invention provides a method and a device for detecting a moving target object and a storage medium, which reduce the false alarm rate of the moving target object and improve the accuracy rate of moving detection.
A first aspect of the present invention provides a detection method of a moving target object, including:
acquiring a plurality of frames of images, wherein each frame of image comprises at least one target object;
carrying out target object matching on the multi-frame images;
determining the number of continuous moving frames of which the moving distance of the same target object in the multiple frames of images in two adjacent frames of images meets a preset distance range;
and taking the same target object in the image with the number of the continuous moving frames being greater than or equal to a preset threshold value as a moving target object.
In one possible implementation manner, the acquiring the multi-frame image includes:
and acquiring the coordinate position and the selection frame of at least one target object in the multi-frame images.
In a possible implementation manner, the acquiring the coordinate position and the selection frame image of the at least one target object in the multiple frames of images includes:
acquiring a plurality of selection frames corresponding to each target object in each frame of image;
determining a best selection box for each of the target objects from the plurality of selection boxes;
and determining the coordinate position of the optimal selection frame of each target object in each frame image and the selection frame image.
In a possible implementation manner, the performing target object matching on the multi-frame image includes:
for each frame of image, sequencing the target objects according to the area of the optimal selection frame of the target objects;
and performing target object matching on the multi-frame images according to the sequencing result.
In a possible implementation manner, the performing target object matching on the multiple frames of images according to the sorting result includes:
acquiring gray information, pixel area and coordinate position of the optimal selection frame of the first target object corresponding to the same sorting result in each frame of image;
and if the gray difference value of the best selection frame of the first target object in the two adjacent frames of images is smaller than a preset gray difference value, the pixel area difference value is smaller than a preset pixel area difference value, and the coordinate position difference value is smaller than a preset coordinate position difference value, determining that the first target object in the two adjacent frames of images is the same target object.
In a possible implementation manner, the determining the number of consecutive moving frames in which the moving distance of the same target object in the multiple frames of images in two adjacent frames of images meets a preset distance range includes:
when the moving distance of the same target object in two adjacent frames of images is greater than or equal to a first preset distance and the moving distance is less than or equal to a second preset distance, adding one to the number of continuous moving frames of the same target object;
and determining the number of continuous moving frames of the same target object in the multi-frame image.
In a possible implementation manner, after the same target object in the image of which the number of consecutive moving frames is greater than or equal to the preset threshold is taken as the moving target object, the method further includes:
and pushing a moving target detection result, wherein the moving target detection result comprises an image and a motion track of the moving target object.
A second aspect of the present invention provides a detection apparatus of a moving target object, including:
the device comprises an acquisition module, a processing module and a display module, wherein the acquisition module is used for acquiring a plurality of frames of images, and each frame of image comprises at least one target object;
the matching module is used for matching the target object of the multi-frame image;
the determining module is used for determining the number of continuous moving frames of which the moving distance of the same target object in the multi-frame images in two adjacent frames of images meets a preset distance range;
the determining module is further configured to use the same target object in the image with the number of the consecutive moving frames being greater than or equal to a preset threshold as a moving target object.
A third aspect of the present invention provides a detection apparatus of a moving target object, comprising:
a memory;
a processor; and
a computer program;
wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method according to any one of the first aspect of the invention.
A fourth aspect of the invention provides a computer readable storage medium having stored thereon a computer program for execution by a processor to perform the method according to any one of the first aspect of the invention.
The embodiment of the invention provides a method and a device for detecting a moving target object and a storage medium. The method comprises the following steps: acquiring multi-frame images, performing target object matching on the multi-frame images, determining the number of continuous moving frames in which the moving distance of the same target object in the multi-frame images in two adjacent frames of images meets a preset distance range, and determining the same target object as a moving target object if the number of the continuous moving frames is larger than or equal to a preset threshold value. The method introduces the moving distance of the same target object, counts the number of moving frames of the same target object moving continuously in the multi-frame images according to the moving distance, greatly reduces the false alarm rate of the moving target object, and improves the accuracy rate of moving detection.
Drawings
Fig. 1 is a schematic flow chart of a method for detecting a moving target object according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a selection box for obtaining a target object by object detection according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of overlapped selection boxes according to an embodiment of the present invention;
fig. 4 is a functional structure diagram of a detection apparatus for a moving target object according to an embodiment of the present invention;
fig. 5 is a functional structure diagram of a detection apparatus for a moving target object according to another embodiment of the present invention;
fig. 6 is a schematic hardware structure diagram of a detection apparatus for a moving target object according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the invention, as detailed in the appended claims.
The terms "comprising" and "having," and any variations thereof, in the description and claims of this invention are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference throughout this specification to "one embodiment" or "another embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present application. Thus, the appearances of the phrases "in some embodiments" or "in this embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
Fig. 1 is a schematic flow chart of a method for detecting a moving target object according to an embodiment of the present invention, fig. 2 is a schematic diagram of a selection frame of a target object obtained by object detection according to an embodiment of the present invention, and fig. 3 is a schematic diagram of mutually overlapped selection frames according to an embodiment of the present invention.
The detection method provided by this embodiment may be performed by any device that performs the method, and the device may be a video acquisition end device, such as a video camera, a still camera, or the like, or may be a service end, such as a video monitoring platform, or the like. The apparatus may be implemented by software and/or hardware.
As shown in fig. 1, the detection method provided by this embodiment includes:
In this embodiment, acquiring the multi-frame image includes: and acquiring the coordinate position and the selection frame of at least one target object in the multi-frame images. Wherein the coordinate position of the target object refers to the coordinate position of the target object in the image. The coordinate origin of the image can be set at the center of the image, and correspondingly, the coordinate position of the target object in the image can be understood as the coordinate position of any top corner (upper left corner, upper right corner, lower left corner or lower right corner) of the selection frame corresponding to the target object relative to the center of the image.
For each frame of image, one or more target objects may be included in the image. For each target object, a plurality of selection frames corresponding to the target object can be obtained by using a classical object detection method, such as a sliding window method. As shown in fig. 2, assuming that a certain frame image only includes one car, 3 selection frames, namely selection frames 1, 2, and 3, corresponding to the car can be obtained by using a sliding window method.
It can be understood that if each target object in each frame of image includes a plurality of corresponding selection frames, the amount of data to be processed by the detection apparatus in the subsequent target object matching process will be very large, and therefore, a large amount of memory space and a high-performance CPU are required to ensure the data processing rate.
In order to solve the above problem, optionally, before performing target object matching on a plurality of frames of images, the acquired plurality of frames of images may be preprocessed to remove unnecessary selection frames of the target object, so as to reduce the data amount in the target object matching process.
In one possible implementation manner, acquiring the coordinate position and the selection frame image of the at least one target object in the multi-frame image may include: acquiring a plurality of selection frames corresponding to each target object in each frame of image; determining an optimal selection frame for each target object from the plurality of selection frames; and determining the coordinate position of the optimal selection frame of each target object in each frame image and the selection frame image.
Specifically, a plurality of selection frames corresponding to each target object in each frame of image are obtained; non-maximum suppression is used to determine the best selection box for each target object from the plurality of selection boxes. The principle of non-maximum suppression is as follows: selecting the selection frame with the maximum score from the selection frame list of the same target object, removing the selection frame with the maximum score from the selection frame list, adding the selection frame into a final detection result, respectively calculating the intersection ratio IOU of the rest selection frames in the selection frame list and the selection frame with the maximum score, removing the selection frame with the IOU larger than a preset threshold value from the selection frame list, and repeating the process until the selection frame list is empty.
It should be noted that the preset threshold of the IOU may be set according to actual requirements, and the higher the preset threshold is set, the greater the number of selection frames of the same target object is.
As shown in fig. 3, assuming that the pixel area of the frame 1 of the target object is S1, the pixel area of the frame 2 of the target object is S2, where the frame 2 is the largest scoring frame, and the pixel area of the overlapping portion of the frame 1 and the frame 2 is S3, the intersection ratio IOU1 of the frame 1 to the frame 2 is S3/(S1+ S2-S3). Assuming that the value of IOU1 is 0.5 and the preset threshold value of IOU is 0.4, since the value of IOU1 is greater than the preset threshold value of IOU, redundant checkbox 1 is deleted.
And 102, performing target object matching on the multi-frame image.
In this embodiment, for each frame of image, the target objects are sorted according to the area of the optimal selection frame of the target objects; and matching the target objects of the multi-frame images according to the sequencing result. For example, assume that each of the multi-frame images includes 3 target objects, namely the target object A, B, C. The coordinate position of the best selection box and the selection box image of each target object in each frame image can be determined according to step 101. In the process of performing target object matching, the target objects are sorted according to the area size of the optimal selection box of the target objects, for example, the pixel areas of the target object A, B, C in the first frame image are respectively SA，SB，SCThe result of the sorting is SB>SA>SC. And respectively carrying out target object matching on the target object B, the target object A and the target object C in the multi-frame images according to the sequencing result. The above process reduces the calculation amount of object matching and reduces the consumption of memory resources.
Further, acquiring gray information, pixel area and coordinate position of the optimal selection frame of the first target object corresponding to the same sorting result in each frame of image; and if the gray difference value of the best selection frame of the first target object in the two adjacent frames of images is smaller than the preset gray difference value, the pixel area difference value is smaller than the preset pixel area difference value, and the coordinate position difference value is smaller than the preset coordinate position difference value, determining that the first target object in the two adjacent frames of images is the same target object. Based on the above example, whether the target objects B, a target object a, and a target object C in the multi-frame images are the same target object, are respectively determined according to the sorting result.
In the present embodiment, the gradation information of the optimal selection frame of the target object may be acquired by a gradation histogram. The gray histogram is a function of gray level distribution, and is a statistic of gray level distribution in an image. The gray histogram is to count the occurrence frequency of all pixels in the digital image according to the size of the gray value. The gray histogram is a function of gray level, which represents the number of pixels in an image having a certain gray level, reflecting the frequency of occurrence of a certain gray level in the image.
And 103, determining the number of continuous moving frames of which the moving distance of the same target object in the multi-frame images in two adjacent frames of images meets a preset distance range.
Specifically, after the target object matching is performed on the multiple frame images, for the same target object in the multiple frame images, the moving distance of the same target object in two adjacent frame images is determined. The moving distance can be determined by the coordinate position of the same target object in the two adjacent images, and the moving distance comprises a horizontal moving distance and/or a vertical moving distance. If the moving distance is greater than or equal to a first preset distance and less than or equal to a second preset distance, adding one to the number of continuous moving frames of the target object; and determining the number of continuous moving frames of the same target object in the multi-frame images.
And 104, taking the same target object in the image with the number of the continuous moving frames larger than or equal to a preset threshold value as a moving target object.
Illustratively, the preset threshold is set to m frames, and if the continuous moving frames of the target object a in the n frames of images are m +1 frames, the target object a is a moving target object; if the continuous moving frame of the target object B in the n frames of images is m-2 frames, the target object B is not a moving target object.
The method for detecting the moving target object provided by the embodiment of the invention is characterized in that target object matching is carried out on multiple frames of images by obtaining the multiple frames of images, the number of continuous moving frames in which the moving distance of the same target object in the multiple frames of images in two adjacent frames of images meets a preset distance range is determined, and if the number of the continuous moving frames is larger than or equal to a preset threshold value, the same target object is determined to be the moving target object. The method introduces the moving distance of the same target object, counts the number of moving frames of the same target object moving continuously in the multi-frame images according to the moving distance, greatly reduces the false alarm rate of the moving target object, and improves the accuracy rate of moving detection.
Optionally, on the basis of the foregoing embodiment, after determining that the same target object in the multiple frames of images is the moving target object, the method may further include:
and pushing a moving target detection result.
The moving target detection result comprises an image and a motion trail of the moving target object.
The executing device of this embodiment may be a video collecting device, and after the video collecting device determines that the same target object in multiple frames of images is a moving target object, the video collecting device reports a moving target detection result to the video monitoring platform, so that the video monitoring platform triggers an alarm according to the received moving target detection result, and the alarm mode includes sound, an indicator light, a short message, a telephone, and the like.
Of course, the video monitoring platform may also determine whether a moving target object exists directly according to the detection method of this embodiment, and trigger an alarm after determining that the moving target object exists.
Fig. 4 is a functional structure diagram of a detection apparatus for a moving target object according to an embodiment of the present invention. As shown in fig. 4, the detection apparatus 400 for a moving target object according to the present embodiment includes:
an obtaining module 401, configured to obtain multiple frames of images, where each frame of image includes at least one target object;
a matching module 402, configured to perform target object matching on the multiple frames of images;
a determining module 403, configured to determine the number of consecutive moving frames in which a moving distance of the same target object in the multiple frames of images in two adjacent frames of images meets a preset distance range;
the determining module 403 is further configured to use the same target object in the image with the number of consecutive moving frames being greater than or equal to a preset threshold as the moving target object.
The detection device for the moving target object provided by the embodiment of the invention comprises an acquisition module, a matching module and a determination module. The acquisition module is used for acquiring multi-frame images; the matching module is used for matching the target object for the multi-frame image; the determining module is used for determining the number of continuous moving frames of which the moving distance of the same target object in the multiple frames of images in the two adjacent frames of images meets the preset distance range, and if the number of the continuous moving frames is larger than or equal to a preset threshold value, determining that the same target object is a moving target object. The device introduces the moving distance of the same target object, counts the number of moving frames of the continuous movement of the same target object in the multi-frame images according to the moving distance, greatly reduces the false alarm rate of the moving target object, and improves the accuracy rate of the moving detection.
Optionally, in a possible implementation manner, the obtaining module 401 is specifically configured to:
and acquiring the coordinate position and the selection frame of at least one target object in the multi-frame images.
Optionally, in a possible implementation manner, the obtaining module 401 is specifically configured to:
acquiring a plurality of selection frames corresponding to each target object in each frame of image;
determining a best selection box for each of the target objects from the plurality of selection boxes;
and determining the coordinate position of the optimal selection frame of each target object in each frame image and the selection frame image.
Optionally, in a possible implementation manner, the matching module 402 is specifically configured to:
for each frame of image, sequencing the target objects according to the area of the optimal selection frame of the target objects;
and performing target object matching on the multi-frame images according to the sequencing result.
Optionally, in a possible implementation manner, the obtaining module 401 is further configured to:
acquiring gray information, pixel area and coordinate position of the optimal selection frame of the first target object corresponding to the same sorting result in each frame of image;
the determining module 403 is specifically configured to:
and if the gray difference value of the best selection frame of the first target object in the two adjacent frames of images is smaller than a preset gray difference value, the pixel area difference value is smaller than a preset pixel area difference value, and the coordinate position difference value is smaller than a preset coordinate position difference value, determining that the first target object in the two adjacent frames of images is the same target object.
Optionally, in a possible implementation manner, the determining module 403 is specifically configured to:
when the moving distance of the same target object in two adjacent frames of images is greater than or equal to a first preset distance and the moving distance is less than or equal to a second preset distance, adding one to the number of continuous moving frames of the same target object;
and determining the number of continuous moving frames of the same target object in the multi-frame image.
Fig. 5 is a functional structure diagram of a detection apparatus for a moving target object according to another embodiment of the present invention. On the basis of the embodiment shown in fig. 4, the detection apparatus 400 provided in this embodiment further includes: a push module 404.
The pushing module 404 is configured to: and after the same target object in the images with the number of the continuous moving frames being greater than or equal to the preset threshold value is taken as a moving target object, pushing a moving target detection result, wherein the moving target detection result comprises the image and the motion trail of the moving target object.
The detection apparatus provided in this embodiment may implement the technical solutions of the above method embodiments, and the implementation principles and technical effects thereof are similar, and are not described herein again.
Fig. 6 is a schematic hardware structure diagram of a detection apparatus for a moving target object according to an embodiment of the present invention. As shown in fig. 6, the detection apparatus 600 for a moving target object according to the present embodiment includes:
a memory 601;
a processor 602; and
a computer program;
wherein the computer program is stored in the memory 601 and configured to be executed by the processor 602 to implement the technical solution of any one of the foregoing method embodiments, and the implementation principle and technical effect thereof are similar, and are not described herein again.
Alternatively, the memory 601 may be separate or integrated with the processor 602.
When the memory 601 is a device independent from the processor 602, the detection apparatus 600 further includes:
a bus 603 for connecting the memory 601 and the processor 602.
Embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by the processor 602 to implement the steps performed by the detection apparatus 600 in the above method embodiments.
It should be understood that the Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor, or in a combination of the hardware and software modules within the processor.
The memory may comprise a high-speed RAM memory, and may further comprise a non-volatile storage NVM, such as at least one disk memory, and may also be a usb disk, a removable hard disk, a read-only memory, a magnetic or optical disk, etc.
The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, the buses in the figures of the present application are not limited to only one bus or one type of bus.
The storage medium may be implemented by any type or combination of volatile or non-volatile memory devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an Application Specific Integrated Circuits (ASIC). Of course, the processor and the storage medium may reside as discrete components in the detection apparatus.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A method of detecting a moving target object, comprising:
acquiring a plurality of frames of images, wherein each frame of image comprises at least one target object;
carrying out target object matching on the multi-frame images;
determining the number of continuous moving frames of which the moving distance of the same target object in the multiple frames of images in two adjacent frames of images meets a preset distance range;
and taking the same target object in the image with the number of the continuous moving frames being greater than or equal to a preset threshold value as a moving target object.
2. The method of claim 1, wherein the acquiring the plurality of frames of images comprises: and acquiring the coordinate position and the selection frame of at least one target object in the multi-frame images.
3. The method according to claim 2, wherein the acquiring the coordinate position and the selection frame image of the at least one target object in the multi-frame images comprises:
acquiring a plurality of selection frames corresponding to each target object in each frame of image;
determining a best selection box for each of the target objects from the plurality of selection boxes;
and determining the coordinate position of the optimal selection frame of each target object in each frame image and the selection frame image.
4. The method according to claim 1, wherein the performing target object matching on the multi-frame image comprises:
for each frame of image, sequencing the target objects according to the area of the optimal selection frame of the target objects;
and performing target object matching on the multi-frame images according to the sequencing result.
5. The method according to claim 4, wherein the performing target object matching on the plurality of frames of images according to the sequencing result comprises:
acquiring gray information, pixel area and coordinate position of the optimal selection frame of the first target object corresponding to the same sorting result in each frame of image;
and if the gray difference value of the best selection frame of the first target object in the two adjacent frames of images is smaller than a preset gray difference value, the pixel area difference value is smaller than a preset pixel area difference value, and the coordinate position difference value is smaller than a preset coordinate position difference value, determining that the first target object in the two adjacent frames of images is the same target object.
6. The method according to claim 1, wherein the determining the number of consecutive moving frames in which the moving distance of the same target object in the multiple frames of images in two adjacent frames of images meets a preset distance range comprises:
when the moving distance of the same target object in two adjacent frames of images is greater than or equal to a first preset distance and the moving distance is less than or equal to a second preset distance, adding one to the number of continuous moving frames of the same target object;
and determining the number of continuous moving frames of the same target object in the multi-frame image.
7. The method according to claim 1, wherein after the same target object in the image with the number of consecutive moving frames greater than or equal to a preset threshold is taken as a moving target object, the method further comprises:
and pushing a moving target detection result, wherein the moving target detection result comprises an image and a motion track of the moving target object.
8. A moving target object detection apparatus, comprising:
the device comprises an acquisition module, a processing module and a display module, wherein the acquisition module is used for acquiring a plurality of frames of images, and each frame of image comprises at least one target object;
the matching module is used for matching the target object of the multi-frame image;
the determining module is used for determining the number of continuous moving frames of which the moving distance of the same target object in the multi-frame images in two adjacent frames of images meets a preset distance range;
the determining module is further configured to use the same target object in the image with the number of the consecutive moving frames being greater than or equal to a preset threshold as a moving target object.
9. A moving target object detection apparatus, comprising:
a memory;
a processor; and
a computer program;
wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method of any one of claims 1-7.
10. A computer-readable storage medium, having stored thereon a computer program for execution by a processor to perform the method of any one of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910725138.0A CN112347810A (en) | 2019-08-07 | 2019-08-07 | Method and device for detecting moving target object and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910725138.0A CN112347810A (en) | 2019-08-07 | 2019-08-07 | Method and device for detecting moving target object and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112347810A true CN112347810A (en) | 2021-02-09 |
Family
ID=74366655
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910725138.0A Pending CN112347810A (en) | 2019-08-07 | 2019-08-07 | Method and device for detecting moving target object and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112347810A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113378958A (en) * | 2021-06-24 | 2021-09-10 | 北京百度网讯科技有限公司 | Automatic labeling method, device, equipment, storage medium and computer program product |
| CN113485579A (en) * | 2021-06-30 | 2021-10-08 | 东莞市小精灵教育软件有限公司 | Finger stable frame detection method and device and computer readable storage medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104966045A (en) * | 2015-04-02 | 2015-10-07 | 北京天睿空间科技有限公司 | Video-based airplane entry-departure parking lot automatic detection method |
| CN105261035A (en) * | 2015-09-15 | 2016-01-20 | 杭州中威电子股份有限公司 | Method and device for tracking moving objects on highway |
| CN108072385A (en) * | 2017-12-06 | 2018-05-25 | 爱易成技术(天津)有限公司 | Space coordinates localization method, device and the electronic equipment of mobile target |
| CN109819206A (en) * | 2017-11-20 | 2019-05-28 | 纬创资通股份有限公司 | Object method for tracing and its system and computer-readable storage medium based on image |
| CN109841022A (en) * | 2018-11-29 | 2019-06-04 | 广州紫川物联网科技有限公司 | A kind of target motion track detecting/warning method, system and storage medium |
| CN109871760A (en) * | 2019-01-15 | 2019-06-11 | 北京奇艺世纪科技有限公司 | A kind of Face detection method, apparatus, terminal device and storage medium |
-
2019
- 2019-08-07 CN CN201910725138.0A patent/CN112347810A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104966045A (en) * | 2015-04-02 | 2015-10-07 | 北京天睿空间科技有限公司 | Video-based airplane entry-departure parking lot automatic detection method |
| CN105261035A (en) * | 2015-09-15 | 2016-01-20 | 杭州中威电子股份有限公司 | Method and device for tracking moving objects on highway |
| CN109819206A (en) * | 2017-11-20 | 2019-05-28 | 纬创资通股份有限公司 | Object method for tracing and its system and computer-readable storage medium based on image |
| CN108072385A (en) * | 2017-12-06 | 2018-05-25 | 爱易成技术(天津)有限公司 | Space coordinates localization method, device and the electronic equipment of mobile target |
| CN109841022A (en) * | 2018-11-29 | 2019-06-04 | 广州紫川物联网科技有限公司 | A kind of target motion track detecting/warning method, system and storage medium |
| CN109871760A (en) * | 2019-01-15 | 2019-06-11 | 北京奇艺世纪科技有限公司 | A kind of Face detection method, apparatus, terminal device and storage medium |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113378958A (en) * | 2021-06-24 | 2021-09-10 | 北京百度网讯科技有限公司 | Automatic labeling method, device, equipment, storage medium and computer program product |
| CN113485579A (en) * | 2021-06-30 | 2021-10-08 | 东莞市小精灵教育软件有限公司 | Finger stable frame detection method and device and computer readable storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9311533B2 (en) | Device and method for detecting the presence of a logo in a picture | |
| US10070053B2 (en) | Method and camera for determining an image adjustment parameter | |
| CN109409238B (en) | Obstacle detection method and device and terminal equipment | |
| CN105631418A (en) | People counting method and device | |
| US20180047271A1 (en) | Fire detection method, fire detection apparatus and electronic equipment | |
| CN113628404A (en) | Method and device for reducing invalid alarm | |
| CN112348686B (en) | Claim settlement picture acquisition method and device and communication equipment | |
| CN112347810A (en) | Method and device for detecting moving target object and storage medium | |
| CN112330715A (en) | Tracking method, tracking device, terminal equipment and readable storage medium | |
| CN100375530C (en) | Movement detecting method | |
| CN111401239B (en) | Video analysis method, device, system, equipment and storage medium | |
| CN114445768A (en) | Target identification method and device, electronic equipment and storage medium | |
| CN114708426A (en) | Target detection method, model training method, device, equipment and storage medium | |
| CN111401315B (en) | Face recognition method based on video, recognition device and storage device | |
| CN113920585A (en) | Behavior recognition method and device, equipment and storage medium | |
| CN110807457A (en) | OSD character recognition method, device and storage device | |
| JP2001160146A (en) | Method and device for recognizing image | |
| CN116246298A (en) | Space occupation people counting method, terminal equipment and storage medium | |
| CN114898279A (en) | Object detection method and device, computer equipment and storage medium | |
| JP6591349B2 (en) | Motion detection system and motion detection method | |
| CN111027560B (en) | Text detection method and related device | |
| CN114419531A (en) | Object detection method, object detection system, and computer-readable storage medium | |
| CN107886102B (en) | Adaboost classifier training method and system | |
| JPH11203567A (en) | Image processor for monitor | |
| CN113435352B (en) | Civilized city scoring method and device, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |