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Object detection is broadly utilized in robotic navigation, clever video surveillance, industrial inspection, aerospace and plenty of different fields. It is a crucial branch of image processing and pc vision disciplines, and is also the core part of clever surveillance methods. At the same time, target detection is also a fundamental algorithm in the sector of pan-identification, which performs a vital role in subsequent duties reminiscent of face recognition, gait recognition, crowd counting, and occasion segmentation. After the first detection module performs target detection processing on the video body to obtain the N detection targets in the video body and the first coordinate info of every detection goal, the above technique It additionally contains: displaying the above N detection targets on a display screen. The primary coordinate info corresponding to the i-th detection goal; acquiring the above-mentioned video body; positioning within the above-talked about video frame in line with the primary coordinate information corresponding to the above-mentioned i-th detection target, obtaining a partial image of the above-talked about video body, and determining the above-mentioned partial image is the i-th picture above.

The expanded first coordinate data corresponding to the i-th detection target; the above-mentioned first coordinate info corresponding to the i-th detection target is used for positioning within the above-mentioned video body, including: based on the expanded first coordinate data corresponding to the i-th detection target The coordinate information locates within the above video body. Performing object detection processing, if the i-th picture includes the i-th detection object, ItagPro buying position info of the i-th detection object in the i-th image to obtain the second coordinate information. The second detection module performs goal detection processing on the jth picture to determine the second coordinate data of the jth detected goal, where j is a constructive integer not better than N and never equal to i. Target detection processing, obtaining a number of faces in the above video body, iTagPro smart tracker and first coordinate information of each face; randomly obtaining target faces from the above multiple faces, and intercepting partial images of the above video frame in accordance with the above first coordinate data ; performing target detection processing on the partial image by means of the second detection module to obtain second coordinate information of the goal face; displaying the goal face in response to the second coordinate info.

Display a number of faces in the above video body on the display. Determine the coordinate list in keeping with the primary coordinate info of each face above. The first coordinate data corresponding to the target face; acquiring the video body; and positioning within the video frame in keeping with the first coordinate data corresponding to the goal face to acquire a partial picture of the video frame. The prolonged first coordinate information corresponding to the face; the above-talked about first coordinate data corresponding to the above-mentioned target face is used for positioning in the above-talked about video body, including: iTagPro smart tracker based on the above-talked about extended first coordinate information corresponding to the above-talked about goal face. Within the detection process, if the partial image includes the goal face, buying place info of the goal face within the partial image to acquire the second coordinate info. The second detection module performs goal detection processing on the partial image to determine the second coordinate info of the other target face.