Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...
The problem of extracting information from large collections of imagery is a challenge with few good solutions. Computers typically cannot interpret imagery as effectively as huma...
Santosh Mathan, Deniz Erdogmus, Yonghong Huang, Mi...
This paper presents a supervised manifold learning model for dimensionality reduction in image and video classification tasks. Unlike most manifold learning models that emphasize ...
The problem of face detection remains challenging because faces are non-rigid objects that have a high degree of variability with respect to head rotation, illumination, facial ex...
We present a method for interactive rendering of large outdoor scenes. Complex polygonal plant models and whole plant populations are represented by relatively small sets of point...
Oliver Deussen, Carsten Colditz, Marc Stamminger, ...