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A joint mechanism algorithm for object detection
Author(s): Zhuo Han; Dongfei Wang; Aidong Men; Yun Zhou
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Paper 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.

Paper Details

Date Published: 6 May 2019
PDF: 7 pages
Proc. SPIE 11069, Tenth International Conference on Graphics and Image Processing (ICGIP 2018), 110693X (6 May 2019); doi: 10.1117/12.2524207
Show Author Affiliations
Zhuo Han, Beijing Univ. of Posts and Telecommunications (China)
Dongfei Wang, Academy of Broadcasting Science (China)
Aidong Men, Beijing Univ. of Posts and Telecommunications (China)
Yun Zhou, Academy of Broadcasting Science (China)


Published in SPIE Proceedings Vol. 11069:
Tenth International Conference on Graphics and Image Processing (ICGIP 2018)
Chunming Li; Hui Yu; Zhigeng Pan; Yifei Pu, Editor(s)

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