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Implementation of Moving Object Recognition based on Deep Learning  

Lee, YuKyong (Dept. of Smart Phone Media, BaekSeok Culture University)
Lee, Yong-Hwan (Dept. of Digital Contents, Wonkwang University)
Publication Information
Journal of the Semiconductor & Display Technology / v.17, no.2, 2018 , pp. 67-70 More about this Journal
Abstract
Object detection and tracking is an exciting and interesting research area in the field of computer vision, and its technologies have been widely used in various application systems such as surveillance, military, and augmented reality. This paper proposes and implements a novel and more robust object recognition and tracking system to localize and track multiple objects from input images, which estimates target state using the likelihoods obtained from multiple CNNs. As the experimental result, the proposed algorithm is effective to handle multi-modal target appearances and other exceptions.
Keywords
Object Detection and Tracking; Object Recognition; Moving Object; Deep Learning; CNN(Convolution Neural Network);
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