Real world computer vision systems highly depend on reliable, robust retrieval of motion cues to make accurate decisions about their surroundings. In this paper, we present a simp...
In this work, we propose an unsupervised Bayesian model for the detection of moving objects from dynamic scenes. This unsupervised solution is a three-step approach that uses a st...
Autonomous robots use sensors to perceive and track objects in the world. Tracking algorithms use object motion models to estimate the position of a moving object. Tracking effic...
We present an approach to 3D scene flow estimation, which exploits that in realistic scenarios image motion is frequently dominated by observer motion and independent, but rigid ...
We present a Bayesian approach to image-based visual hull reconstruction. The 3-D shape of an object of a known class is represented by sets of silhouette views simultaneously obs...
Kristen Grauman, Gregory Shakhnarovich, Trevor Dar...