We present an unsupervised technique for detecting unusual activity in a large video set using many simple features. No complex activity models and no supervised feature selection...
We boost the efficiency and robustness of distributionbased matching by random subsampling which results in the minimum number of samples required to achieve a specified probabili...
Models of activity structure for unconstrained environments are generally not available a priori. Recent representational approaches to this end are limited by their computational...
Raffay Hamid, Siddhartha Maddi, Aaron F. Bobick, I...
Abstract. Establishing correspondence between features of a set of images has been a long-standing issue amongst the computer vision community. We propose a method that solves the ...
We propose a fast approach to 3?D object detection and pose estimation that owes its robustness to a training phase during which the target object slowly moves with respect to the ...