A kind of Rapid Robust Human Detection Algorithm for the Interested Area
- DOI
- 10.2991/icaset-17.2017.20How to use a DOI?
- Keywords
- Human detection, Expanded multi-scale direction feature, Nonnegative matrix decomposition, Intersection kernel support vector machine
- Abstract
A kind of rapid two-level human detection algorithm based on the interested area was proposed in the paper, the coarse-level classifier was obtained via using the cascade training of multi-scale direction feature and Adaboost to extract the possibly human interested area, the decomposition and dimension reduction were realized via nonnegative matrix, and the précised classifier was obtained via the cascade training of dimension reduction feature and intersection kernel support vector machine to detect the human precisely. The experiment on INRIA public test set showed that the algorithm proposed in the paper improved the detection accuracy and greatly reduced the detection time when compared with the currently representative algorithm.
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Xiaoting Chen AU - Yuan Shen AU - Jing Yin AU - Dongcai Liu AU - Xiaohu Zhao AU - Feng Chang PY - 2017/05 DA - 2017/05 TI - A kind of Rapid Robust Human Detection Algorithm for the Interested Area BT - Proceedings of the 2017 7th International Conference on Applied Science, Engineering and Technology (ICASET 2017) PB - Atlantis Press SP - 108 EP - 111 SN - 2352-5401 UR - https://doi.org/10.2991/icaset-17.2017.20 DO - 10.2991/icaset-17.2017.20 ID - Chen2017/05 ER -