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Object detection is widely used in robot 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 a part of intelligent surveillance methods. At the same time, goal detection is also a fundamental algorithm in the sphere of pan-identification, which performs an important position in subsequent duties resembling face recognition, gait recognition, crowd counting, iTagPro reviews and instance segmentation. After the primary detection module performs goal detection processing on the video frame to obtain the N detection targets within the video body and the primary coordinate information of every detection target, the above method It also includes: displaying the above N detection targets on a screen. The first coordinate information corresponding to the i-th detection target; obtaining the above-mentioned video body; positioning in the above-mentioned video frame in response to the primary coordinate info corresponding to the above-mentioned i-th detection target, acquiring a partial image of the above-mentioned video frame, and determining the above-talked about partial picture is the i-th picture above.

The expanded first coordinate information corresponding to the i-th detection target; the above-talked about first coordinate info corresponding to the i-th detection goal is used for positioning within the above-mentioned video body, together with: in keeping with the expanded first coordinate data corresponding to the i-th detection goal The coordinate info locates in the above video frame. Performing object detection processing, ItagPro if the i-th image consists of the i-th detection object, buying position information of the i-th detection object within the i-th image to obtain the second coordinate info. The second detection module performs target detection processing on the jth image to find out the second coordinate info of the jth detected goal, the place j is a positive integer not better than N and never equal to i. Target detection processing, acquiring multiple faces within the above video body, and iTagPro online first coordinate information of each face; randomly obtaining target faces from the above multiple faces, and intercepting partial pictures of the above video frame based on the above first coordinate information ; performing goal detection processing on the partial image by the second detection module to acquire second coordinate information of the goal face; displaying the target face based on the second coordinate info.

Display a number of faces within the above video frame on the display. Determine the coordinate checklist in response to the primary coordinate info of each face above. The primary coordinate information corresponding to the goal face; acquiring the video frame; and positioning within the video frame in accordance with the primary coordinate information corresponding to the goal face to acquire a partial picture of the video body. The extended first coordinate data corresponding to the face; the above-mentioned first coordinate information corresponding to the above-talked about goal face is used for positioning in the above-mentioned video frame, together with: according to the above-talked about extended first coordinate data corresponding to the above-mentioned goal face. In the detection course of, if the partial image consists of the goal face, buying position data of the target face within the partial image to obtain the second coordinate information. The second detection module performs goal detection processing on the partial image to determine the second coordinate information of the other goal face.