Representation of local geometry in the visual system
Biological Cybernetics
The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Recursive implementation of the Gaussian filter
Signal Processing
Bricks: laying the foundations for graspable user interfaces
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
mediaBlocks: physical containers, transports, and controls for online media
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Feature Detection with Automatic Scale Selection
International Journal of Computer Vision
Estimating the Pose of Phicons for Human Computer Interaction
ICMI '00 Proceedings of the Third International Conference on Advances in Multimodal Interfaces
Perceptual Components for Context Aware Computing
UbiComp '02 Proceedings of the 4th international conference on Ubiquitous Computing
Computer Vision and Image Understanding
Hi-index | 0.00 |
This paper describes an extension of a technique for the recognition and tracking of every day objects in cluttered scenes. The goal is to build a system in which ordinary desktop objects serve as physical icons in a vision based system for man-machine interaction. In such a system, the manipulation of objects replaces user commands. A view-variant recognition technique, developed by the second author, has been adapted by the first author for a problem of recognising and tracking objects on a cluttered background in the presence of occlusions. This method is based on sampling a local appearance function at discrete viewpoints by projecting it onto a vector of receptive fields which have been normalised to local scale and orientation. This paper reports on the experimental validation of the approach, and of its extension to the use of receptive fields based on colour. The experimental results indicate that the second author's technique does indeed provide a method for building a fast and robust recognition technique. Furthermore, the extension to coloured receptive fields provides a greater degree of local discrimination and an enhanced robustness to variable background conditions. The approach is suitable for the recognition of general objects as physical icons in an augmented reality.