Title :
Automatic categorization-based multi-stage pedestrian detection
Author :
Yang, Kai ; Du, Eliza Yingzi ; Jiang, Pingge ; Chen, Yaobin ; Sherony, Rini ; Takahashi, Hiroyuki
Author_Institution :
Dept. of Electr. & Comput. Eng., Indiana Univ.-Purdue Univ., Indianapolis, IN, USA
Abstract :
Pedestrian safety has become an important issue for automobile design. Although a lot of research has been done or is ongoing in developing in-car camera-based pedestrian protection systems, robust and reliable in-car camera based pedestrian analysis is still very challenging, especially for real-time systems or large scale dataset analysis. In this paper, we propose a new pedestrian detection and analysis system based on automatic categorization. A category-based multi-stage pedestrian detection and data analysis approach is developed to efficiently process the extremely large scale driving data collected in this research. The experimental results on part of the collecting dataset show that the proposed method is promising.
Keywords :
automobiles; cameras; data analysis; object detection; pedestrians; road safety; automatic categorization-based multistage pedestrian detection; automobile design; data analysis approach; in-car camera based pedestrian analysis; in-car camera-based pedestrian protection systems; large scale dataset analysis; pedestrian safety; real-time systems; Accuracy; Detection algorithms; Feature extraction; Lighting; Meteorology; Roads; Vehicles; categorization-based pedestrian data analysis; multi-stage pedestrian recognition; pedestrian detection;
Conference_Titel :
Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4673-3064-0
Electronic_ISBN :
2153-0009
DOI :
10.1109/ITSC.2012.6338874