This paper addresses the frame-to-frame data associ- ation 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 …
We propose a principled statistical approach for using 3D information and scene context to reduce the number of false positives in stereo based pedestrian detection. Current pedestrian detection algorithms have focused on improving the …
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 far infra-red video sequence. In a novel application of the hierarchical modelbased motion …
We present a new multi-stage algorithm for car and truck detection from a moving vehicle. The algorithm performs a search for pertinent features in three dimensions, guided by a ground plane and lane boundary estimation sub-system, and assembles …
We describe a low-cost vision-based sensing and positioning system that enables intelligent vehicles of the future to autonomously drive in an urban environment with traffic. The system was built by integrating Sarnoff’s algorithms for driver …
Development of a practical stereo vision sensor for real-world applications must account for the variability of high-volume production processes and the impact of unknown environmental conditions during its operation. One critical factor of stereo …
Modeling a free-form 3D-surface from a single view has been a widely pursued problem. The existing schemes are either fully-automatic shape-from-X techniques or involve adept interaction from the user but little or no geometric (photometric) basis. …
Shape from Shading (SFS) is one of the most extensively studied problems in Computer Vision. However, most of the approaches only deal with Lambertian or other specific shading models, and are hence limited in their applicability to real images. In …