This paper considers a method that combines ideas from Bayesian learning, Bayesian network inference, and classical hypothesis testing to produce a more reliable and robust test o...
This paper proposes a novel approach to shape analysis: using local reasoning about individual heap locations of global reasoning about entire heap abstractions. We present an int...
Principal Component Analysis (PCA) has been widely used to extract features for pattern recognition problems such as object recognition. Oliva and Torralba used “spatial envelop...
In this work, we present an approach to jointly segment a rigid object in a 2D image and estimate its 3D pose, using the knowledge of a 3D model. We naturally couple the two proces...
Samuel Dambreville, Romeil Sandhu, Anthony J. Yezz...
In this paper, we address the problem of learning an
adaptive appearance model for object tracking. In particular,
a class of tracking techniques called “tracking by detectionâ...