14 March 2005 Pixels to objects: a generic vision front-end
Author Affiliations +
Abstract
Vision implies objects, so a vision system front-end needs to produce a feature-based description of image objects. The functional boundaries and specifications for the front-end are derived from analyzing: 1) What feature information can be extracted from context-free video? 2) What feature information will reduce the probability distribution model complexity for statistical object recognition and tracking? 3) How should the feature information be encoded? Segmentation is a flexible tool for extracting features. Recently proposed segmentation algorithms can be adapted to high-performance, low-cost hardware. Inexpensive segmentation will have a multiplying affect on vision system performance/complexity. Two examples are techniques for extending hardware functions into both parallel pixel processes and object tracking.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Craig Sullender, Craig Sullender, } "Pixels to objects: a generic vision front-end", Proc. SPIE 5685, Image and Video Communications and Processing 2005, (14 March 2005); doi: 10.1117/12.585397; https://doi.org/10.1117/12.585397
PROCEEDINGS
15 PAGES


SHARE
RELATED CONTENT

FPGA implementation of real-time digital image stabilization
Proceedings of SPIE (February 20 2014)
Video inpainting using scene model and object tracking
Proceedings of SPIE (February 18 2013)
Video surveillance using distance maps
Proceedings of SPIE (February 14 2006)
A VLSI implementation of CAVLC for H.264/AVC
Proceedings of SPIE (October 30 2009)

Back to Top