An efficient human detection method for multi-pedestrian tracking
来源期刊：中南大学学报(英文版)2013年第12期
论文作者：XU Wei-cun(许伟村) ZHAO Qing-jie(赵清杰) HU Huo-sheng(胡豁生)
文章页码：3552 - 3563
Key words：human detection; spatial proposal filtering; confidential proposal filtering
Abstract: Traditional human detection using pre-trained detectors tends to be computationally intensive for time-critical tracking tasks, and the detection rate is prone to be unsatisfying when occlusion, motion blur and body deformation occur frequently. A spatial-confidential proposal filtering method (SCPF) is proposed for efficient and accurate human detection. It consists of two filtering phases: spatial proposal filtering and confidential proposal filtering. A compact spatial proposal is generated in the first phase to minimize the search space to reduce the computation cost. The human detector only estimates the confidence scores of the candidate search regions accepted by the spatial proposal instead of global scanning. At the second phase, each candidate search region is assigned with a supplementary confidence score according to their reliability estimated by the confidential proposal to reduce missing detections. The performance of the SCPF method is verified by extensive tests on several video sequences from available public datasets. Both quantitatively and qualitatively experimental results indicate that the proposed method can highly improve the efficiency and the accuracy of human detection.
XU Wei-cun(许伟村)1, ZHAO Qing-jie(赵清杰)1, HU Huo-sheng(胡豁生)2
(1. Beijing Key Laboratory of Intelligent Information Technology (School of Computer Science,
Beijing Institute of Technology), Beijing 100081, China;
2. School of Computer Science & Electronic Engineering, University of Essex, Colchester CO4 3SQ, UK)
Abstract:Traditional human detection using pre-trained detectors tends to be computationally intensive for time-critical tracking tasks, and the detection rate is prone to be unsatisfying when occlusion, motion blur and body deformation occur frequently. A spatial-confidential proposal filtering method (SCPF) is proposed for efficient and accurate human detection. It consists of two filtering phases: spatial proposal filtering and confidential proposal filtering. A compact spatial proposal is generated in the first phase to minimize the search space to reduce the computation cost. The human detector only estimates the confidence scores of the candidate search regions accepted by the spatial proposal instead of global scanning. At the second phase, each candidate search region is assigned with a supplementary confidence score according to their reliability estimated by the confidential proposal to reduce missing detections. The performance of the SCPF method is verified by extensive tests on several video sequences from available public datasets. Both quantitatively and qualitatively experimental results indicate that the proposed method can highly improve the efficiency and the accuracy of human detection.
Key words:human detection; spatial proposal filtering; confidential proposal filtering
