In this paper we present a new theory and an algorithm for image segmentation based on a strength of connectedness between every pair of image elements. The object definition use...
Krzysztof Ciesielski, Jayaram K. Udupa, Punam K. S...
We present an approach for object recognition that combines detection and segmentation within a efficient hypothesize/test framework. Scanning-window template classifiers are the ...
Many problems in computer vision involving recognition and/or classification can be posed in the general framework of supervised learning. There is however one aspect of image dat...
Arunava Banerjee, Santhosh Kodipaka, Baba C. Vemur...
Learning visual classifiers for object recognition from weakly labeled data requires determining correspondence between image regions and semantic object classes. Most approaches u...
A Bayesian network formulation for relational shape matching is presented. The main advantage of the relational shape matching approach is the obviation of the non-rigid spatial m...
Anand Rangarajan, James M. Coughlan, Alan L. Yuill...