Pedestrian association and localization in monocular FIR video sequence

This paper addresses the frame-to-frame data association and state estimation problems in localization of a pedestrian relative to a moving vehicle from a monocular far infra-red video sequence. Using a novel application of the hierarchical model-based motion estimation framework, we are able to use...

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Bibliographic Details
Main Authors: Bansal, Mayank, Shunguang Wu, Eledath, Jayan
Format: Conference Proceeding
Language:English
Subjects:
Adaptive filters
Cameras
Filtering algorithms
Finite impulse response filter
Image matching
Matched filters
Motion estimation
State estimation
Vehicles
Video sequences
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Summary:This paper addresses the frame-to-frame data association and state estimation problems in localization of a pedestrian relative to a moving vehicle from a monocular far infra-red video sequence. Using a novel application of the hierarchical model-based motion estimation framework, we are able to use the image appearance information to solve the frame-to-frame data association problem and estimate a sub-pixel accurate height ratio for a pedestrian in two frames. Then, to localize the pedestrian, we propose a novel approach of using the pedestrian height ratio estimates to guide an interacting multiple-hypothesis-mode/height filtering algorithm instead of using a constant pedestrian height model. Experiments on several IR sequences demonstrate that this approach achieves results comparable to those from a known pedestrian height thus avoiding errors from a constant height model based approach.
ISSN:2160-7508
2160-7516
DOI:10.1109/CVPRW.2009.5204132