We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method c...
We describe a new region descriptor and apply it to two problems, object detection and texture classification. The covariance of d-features, e.g., the three-dimensional color vecto...
3D object recognition in scenes with occlusion and clutter is a difficult task. In this paper, we introduce a method that exploits the geometric scale-variability to aid in this ...
The use of image patches to capture local correlations between pixels has been growing in popularity for use in various low-level vision tasks. There is a trade-off between using ...
In this paper we describe a new e cient algorithm for recognizing 3D objects by combining photometric and geometric invariants. Some photometric properties are derived, that are i...