In recent years, sparse representation originating from signal compressed sensing theory has attracted increasing interest in computer vision research community. However, to our b...
This paper describes a machine learning approach for visual
object detection which is capable of processing images
extremely rapidly and achieving high detection rates. This
wor...
We address the normal reconstruction problem by photometric stereo using a uniform and dense set of photometric images captured at fixed viewpoint. Our method is robust to spurio...
We propose a novel unsupervised learning algorithm to extract the layout of an image by learning latent object-related aspects. Unlike traditional image segmentation algorithms th...
We have designed a research platform for a perceptually guided robot, which also serves as a demonstrator for a coming generation of service robots. In order to operate semi-autono...