Abstract
The use of omnidirectional cameras has had a significant impact on the success of vision systems for video surveillance and autonomous robot navigation. Typically images obtained from such cameras are transformed to sparse panoramic images that are interpolated prior to low level image processing. We present a graph theoretic approach that enables image processing techniques, principally feature extraction, to be performed directly on sparse panoramic images, avoiding the need for image interpolation. We thus aim to reduce the computational overheads of processing images arising from omnidirectional cameras, whilst retaining accuracy sufficient for application to real-time robot vision.
Original language | English |
---|---|
Title of host publication | Unknown Host Publication |
Publisher | IEEE Signal Processing Society |
Pages | 1557-1560 |
Number of pages | 4 |
ISBN (Print) | 1-4244-0481-9 |
DOIs | |
Publication status | Published (in print/issue) - Oct 2006 |
Event | IEEE International Conference on Image Processing (ICIP 2006) - Atlanta Duration: 1 Oct 2006 → … |
Conference
Conference | IEEE International Conference on Image Processing (ICIP 2006) |
---|---|
Period | 1/10/06 → … |
Keywords
- feature extraction
- sparse images