14 March 2005 Pixels to objects: a generic vision front-end
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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


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