Stereo-based region of interest generation for real-time pedestrian detection

• Published in: Peer-to-peer networking and applications Vol. 8; no. 2; pp. 181 - 188
• Main Authors: Kim, Joohee, Mesmakhosroshahi, Maral
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01-03-2015; Springer Nature B.V
• Subjects: Accident prevention; Advanced driver assistance systems; Classification; Color; Communications Engineering; Computer Communication Networks; Computer science; Detection alarms; Engineering; Feature extraction; Illumination; Information Systems and Communication Service; Networks; Pedestrians; Platforms; Signal,Image and Speech Processing; Support vector machines; Traffic accidents & safety; Advanced driver assistance system; Pedestrian detection; Stereo vision; ROI generation; Depth map
• ISSN: 1936-6442; 1936-6450
• DOI: 10.1007/s12083-013-0234-2

Pedestrian detection is one of the major goals in advanced driver assistance systems (ADAS) which has become an active research area in recent years. In this paper, we present a stereo based pedestrian detection system by fusing the depth and color data provided by a stereo vision camera on a moving platform. The proposed method uses an adaptive window for region of interest (ROI) generation using dense depth map. The extracted candidates are then applied to a Histogram of Oriented Gradients (HOG) feature descriptor to refine ROIs and Support Vector Machine (SVM) is used to classify them into pedestrian and non-pedestrian classes. The system is tested on a stereo based DAS dataset and results show that our system is able to detect pedestrians with different scales and illumination conditions and in presence of partial occlusion.