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Haiying Liu, Yuncheng Pei, Qiancheng Bei and Lixia Deng
At present, the detection-based pedestrian multi-target tracking algorithm is widely used in artificial intelligence, unmanned driving cars, virtual reality and other fields, and has achieved good tracking results. The traditional DeepSORT algorithm main...
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Yanhua Shao, Xingping Zhang, Hongyu Chu, Xiaoqiang Zhang, Duo Zhang and Yunbo Rao
Aerial object detection acts a pivotal role in searching and tracking applications. However, the large model, limited memory, and computing power of embedded devices restrict aerial pedestrian detection algorithms? deployment on the UAV (unmanned aerial ...
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Liqiang Zhang, Yu Liu and Jinglin Sun
Pedestrian navigation systems could serve as a good supplement for other navigation methods or for extending navigation into areas where other navigation systems are invalid. Due to the accumulation of inertial sensing errors, foot-mounted inertial-senso...
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Dohun Kim, Heegwang Kim, Yeongheon Mok and Joonki Paik
In spite of excellent performance of deep learning-based computer vision algorithms, they are not suitable for real-time surveillance to detect abnormal behavior because of very high computational complexity. In this paper, we propose a real-time surveil...
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Qingge Ji, Haoqiang Yu and Xiao Wu
Based on tracking-by-detection, we propose a hierarchical-matching-based online and real-time multi-object tracking approach with deep appearance features, which can effectively reduce the false positives (FP) in tracking. For the purpose of increasing t...
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