One of the key problems of restoring a degraded image from motion blur is the estimation of the unknown shiftinvariant linear blur filter. Several algorithms have been proposed ut...
Markov Random Field (MRF) models are a popular tool for vision and image processing. Gaussian MRF models are particularly convenient to work with because they can be implemented u...
Marshall F. Tappen, Ce Liu, Edward H. Adelson, Wil...
This paper explores the use of volumetric features for action recognition. First, we propose a novel method to correlate spatio-temporal shapes to video clips that have been autom...
The goal of this paper is to find sparse and representative spatial priors that can be applied to part-based object localization. Assuming a GMRF prior over part configurations, w...
The state-of-the-art object detection algorithm learns a binary classifier to differentiate the foreground object from the background. Since the detection algorithm exhaustively s...
Current approaches to motion category recognition typically focus on either full spatiotemporal volume analysis (holistic approach) or analysis of the content of spatiotemporal in...
In this paper we derive differential equations for evolving radial basis functions (RBFs) to solve segmentation problems. The differential equations result from applying variation...
The compositional nature of visual objects significantly limits their representation complexity and renders learning of structured object models tractable. Adopting this modeling ...