Robust Pedestrian Detection Under Deformation Using Simple Boosted Features
SCIE
SCOPUS
- Title
- Robust Pedestrian Detection Under Deformation Using Simple Boosted Features
- Authors
- Hakkyoung Kim; Daijin Kim
- Date Issued
- 2017-05
- Publisher
- ELSEVIER SCIENCE BV
- Abstract
- Many existing methods for pedestrian detection have the limited detection performance in case of deformation such as large appearance variations. To overcome this limitation, we propose a novel pedestrian detection method that uses two low-level boosted features to detect pedestrians despite the presence of deformations. One is a boosted max feature (BMF) that uses a max operation to aggregate a selected pair of features to make them invariant to deformation. Another is a boosted difference feature (BDF) that uses a difference operation between a selected pair of features to improve localization accuracy of pedestrian detection. We incorporate a spatial pyramid pool method that uses multiple sized blocks to increase the richness of boosted features in a local region and use a RealBoost method to train a tree-structured classifier for the proposed pedestrian detection method. We also apply a region-of-interest method to the detected results to remove false positives effectively. Our proposed detector achieved log-average miss rates of 19.95%, 10.39%, 36.12%, and 39.57% on the Caltech-USA, INRIA, ETH, and TUD-Brussels dataset, respectively, which are the lowest among those of all state-of-the-art pedestrian detectors. (C) 2017 Elsevier B.V. All rights reserved.
- Keywords
- Regionlet; Pedestrian detection; Selective max pooling; Selective difference pooling; Boosted tree-structured classifier
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/38170
- DOI
- 10.1016/j.imavis.2017.02.007
- ISSN
- 0262-8856
- Article Type
- Article
- Citation
- IMAGE AND VISION COMPUTING, vol. 61, page. 1 - 11, 2017-05
- Files in This Item:
- There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.