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Multispectral pedestrian detection: Benchmark dataset and baseline
Cited 546 time in
Web of Science
Cited 743 time in Scopus
- Authors
- Issue Date
- 2015
- Publisher
- IEEE
- Citation
- Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol.07-12-June-2015, pp.1037-1045
- Abstract
- With the increasing interest in pedestrian detection, pedestrian datasets have also been the subject of research in the past decades. However, most existing datasets focus on a color channel, while a thermal channel is helpful for detection even in a dark environment. With this in mind, we propose a multispectral pedestrian dataset which provides well aligned color-thermal image pairs, captured by beam splitter-based special hardware. The color-thermal dataset is as large as previous color-based datasets and provides dense annotations including temporal correspondences. With this dataset, we introduce multispectral ACF, which is an extension of aggregated channel features (ACF) to simultaneously handle color-thermal image pairs. Multi-spectral ACF reduces the average miss rate of ACF by 15%, and achieves another breakthrough in the pedestrian detection task.
- ISSN
- 1063-6919
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