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Chunks: The Remedy for Notorious False Alarms in Pedestrain Detection

Title
Chunks: The Remedy for Notorious False Alarms in Pedestrain Detection
Author
신현철
Keywords
pedestrian detection; occlusion handling; random chunks; ACF-Chunks
Issue Date
2016-01
Publisher
IEEE
Citation
2016 International Conference on Electronics, Information, and Communications (ICEIC), Page. 276-279
Abstract
Though significant progress has been made in last decade but still pedestrian detection is a challenging task. In real world, pedestrians are bound to produce artifacts, like pose & attire variations and occlusions, which are some of the main causes of false alarms. We propose a method which can tackle these variations efficiently. Instead of traditional deformable parts model, we propose random patches (called chunks) to capture the features properties of pedestrians. We have cascaded chunks with Aggregate Channel Features (ACF) detector in order to ratify the pedestrian hypothesis generated by ACF. Our method gives the miss rate of 16.51% at 10-1 false positives per image under reasonable condition, which is among one of the best results achieved on INRIA pedestrian dataset. Our method also improved on the same dataset under partial and heavy occlusion condition.
URI
http://ieeexplore.ieee.org/document/7562956/http://repository.hanyang.ac.kr/handle/20.500.11754/102058
ISBN
978-1-4673-8016-4
DOI
10.1109/ELINFOCOM.2016.7562956
Appears in Collections:
COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > ETC
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