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6 May 2019 A joint mechanism algorithm for object detection
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Proceedings Volume 11069, Tenth International Conference on Graphics and Image Processing (ICGIP 2018); 110693X (2019) https://doi.org/10.1117/12.2524207
Event: Tenth International Conference on Graphic and Image Processing (ICGIP 2018), 2018, Chengdu, China
Abstract
The main goal of object detection is to recognize and locate the object of interest from the static image or video sequence. It is one of the key tasks in the field of computer vision. However, there are many factors in brightness, shape, color and occlusion of targets, and they are disturbed by complex environmental factors, which make the research opportunities and challenges of object detection algorithms coexist. In this paper, two main frameworks of object detection algorithm based on convolutional neural network are researched, which are based on region proposals and regression idea respectively. Then we present a joint mechanism algorithm for object detection. This algorithm makes a balance between detection efficiency and accuracy to make it more meet the actual needs. The internal of the algorithm is adjusted and optimized, so that the two detectors can make their own judgments according to the characteristics of the image, and decide whether to detect the object to classify and locate it, so that the efficiency is higher and the accuracy is also improved.
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Zhuo Han, Dongfei Wang, Aidong Men, and Yun Zhou "A joint mechanism algorithm for object detection", Proc. SPIE 11069, Tenth International Conference on Graphics and Image Processing (ICGIP 2018), 110693X (6 May 2019); https://doi.org/10.1117/12.2524207
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