This paper describes the participation of Idiap-MULTI to the Robot Vision Task at imageCLEF 2010. Our approach was based on a discriminative classification algorithm using multiple...
In this paper we present a framework for semantic scene parsing and object recognition based on dense depth maps. Five viewindependent 3D features that vary with object class are e...
We develop an efficient learning framework to construct signal dictionaries for sparse representation by selecting the dictionary columns from multiple candidate bases. By sparse,...
In this paper, we propose a method based on the skeletonization operation for multi-oriented video text detection. The first step uses our existing Laplacian-based method to ident...
Trung Quy Phan, Palaiahnakote Shivakumara, Chew Li...
Medical volume images contain ambiguous and low-contrast boundaries around which existing fully- or semiautomatic segmentation algorithms often cause errors. In this paper, we pro...