Print Email Facebook Twitter Joint probabilistic pedestrian head and body orientation estimation Title Joint probabilistic pedestrian head and body orientation estimation Author Dumitru-Guzu, M. Contributor Van der Maaten, L.J.P. (mentor) Gavrila, D.M. (mentor) Faculty Electrical Engineering, Mathematics and Computer Science Department Pattern Recognition Programme Media Knowledge and Engineering Date 2014-07-04 Abstract This work presents an approach for joint estimation of the pedestrian head and body orientation in the context of active pedestrian safety systems. It involves a probabilistic framework, where a set of orientation-specific detectors are used for each body part for both localization and orientation estimation, their responses being converted to a continuous orientation probability density function. To improve the localization, spatial anatomical constraints between the head and body are used, in a Pictorial Structure approach, to balance the part-based detector responses. The single-frame head and body orientations are integrated over time by particle filtering and estimated jointly to account for orientation restrictions and to obtain anatomical possible orientation configurations. The experimental evaluation is done over 65 pedestrian tracks in realistic traffic settings, obtained from an external stereo vision-based pedestrian detection system. The results show that the proposed joint probabilistic orientation estimation framework decreases the absolute mean head and body orientation error by approximately 15 degrees. Also, the system runs in near-real-time (8–9 Hz), which allows the use in the car. Subject computer visionorientation estimationactive pedestrian safety To reference this document use: http://resolver.tudelft.nl/uuid:d72b1239-ea0b-45a8-a301-5f9d333f4111 Part of collection Student theses Document type master thesis Rights (c) 2014 Dumitru-Guzu, M. Files PDF MadalinDumitruGuzu_Master ... ersion.pdf 3.28 MB PDF MadalinDumitruGuzu_Workin ... ersion.pdf 5.86 MB Close viewer /islandora/object/uuid:d72b1239-ea0b-45a8-a301-5f9d333f4111/datastream/OBJ1/view