In this paper, we raise important issues on scalability and the required degree of supervision of existing Mahalanobis metric learning methods. Often rather tedious optimization p...
Recent work [5, 6] showed that learning-based patch
rectification methods are both faster and more reliable than
affine region methods. Unfortunately, their performance improveme...
Stefan Hinterstoisser, Oliver Kutter, Nassir Navab...
This paper addresses the problem of capturing the dynamics for exemplar-based recognition systems. Traditional HMM provides a probabilistic tool to capture system dynamics and in ...
Ahmed M. Elgammal, Vinay D. Shet, Yaser Yacoob, La...
In this paper we present a novel approach using a 4D (x,y,z,t) action feature model (4D-AFM) for recognizing actions from arbitrary views. The 4D-AFM elegantly encodes shape and m...
We present a novel framework for learning a joint shape and appearance model from a large set of un-labelled training examples in arbitrary positions and orientations. The shape an...