We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...
Dimensionality reduction via feature projection has been widely used in pattern recognition and machine learning. It is often beneficial to derive the projections not only based o...
We present a higher-level visual representation, visual synset, for object categorization. The visual synset improves the traditional bag of words representation with better discr...
Yantao Zheng, Ming Zhao 0003, Shi-Yong Neo, Tat-Se...
Recently, methods for estimating 3D scene geometry or absolute scene depth information from 2D image content have been proposed. However, general applicability of these methods in...
A new content-based approach for improved H.264/MPEG4-AVC video coding is presented. The framework is generic because it is based on a closed-loop texture analysis by synthesis alg...
Patrick Ndjiki-Nya, Tobias Hinz, Aljoscha Smolic, ...