This paper studies the inference of 3D shape from a set of ? noisy photos. We derive a probabilistic framework to specify what one can infer about 3D shape for arbitrarily-shaped, ...
Rahul Bhotika, David J. Fleet, Kiriakos N. Kutulak...
Piecewise planar models for stereo have recently become popular for modeling indoor and urban outdoor scenes. The strong planarity assumption overcomes the challenges presented by...
The paper presents a fusion-tracker and pedestrian classifier for color and thermal cameras. The tracker builds a background model as a multi-modal distribution of colors and temp...
We present a method for rendering approximate soft shadows and diffuse indirect illumination in dynamic scenes. The proposed method approximates the original scene geometry with a...
Extracting a computer model of a real scene from a sequence of views, is one of the most challenging and fundamental problems in computer vision. Stereo vision algorithms allow us...