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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yali Li Wenhao Lu Shengjin Wang Xiaoqing Ding |
| Copyright Year | 2011 |
| Description | Author affiliation: State Key Laboratory of Intelligent Technology and Systems, Department of Electronic Engineering, Tsinghua University, Beijing, China (Yali Li; Wenhao Lu; Shengjin Wang; Xiaoqing Ding) |
| Abstract | Pedestrian detection is a significant problem in computer vision. Dollar et al. at [1] indicate that current methods are not efficient enough to solve the problem and it remains challenging. Besides, most of the proposed features are also not efficient in describing the features of pedestrians. In this paper, we concentrate on this issue and introduce the local Haar-like features in edge maps to describe the edge/contour of pedestrians efficiently. To reduce the background noise, localized normalization is proposed. Also the integral and tilted integral images are applied to fast extraction of the feature values. The experiments on pedestrian detection show both the describing and computational efficiency of the proposed features. |
| Starting Page | 1424 |
| Ending Page | 1427 |
| File Size | 438556 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424493043 |
| e-ISBN | 9781424493067 |
| DOI | 10.1109/CISP.2011.6100477 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-10-15 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Computer vision Databases Image edge detection pedestrian detection Humans Detectors fast extraction algorithm Feature extraction local Haar-like features Computational efficiency edge features |
| Content Type | Text |
| Resource Type | Article |
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