Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/6027
Title: The Combinatorics of Heuristic Search Termination for Object Recognition in Cluttered Environments
Keywords: computer vision
object recognition
search
combinatorics
Issue Date: 9-Oct-2013
Description: Many recognition systems use constrained search to locate objects in cluttered environments. Earlier analysis showed that the expected search is quadratic in the number of model and data features, if all the data comes from one object, but is exponential when spurious data is included. To overcome this, many methods terminate search once an interpretation that is "good enough" is found. We formally examine the combinatorics of this, showing that correct termination procedures dramatically reduce search. We provide conditions on the object model and the scene clutter such that the expected search is quartic. These results are shown to agree with empirical data for cluttered object recognition.
URI: http://koha.mediu.edu.my:8181/xmlui/handle/1721
Other Identifiers: AIM-1111
http://hdl.handle.net/1721.1/6027
Appears in Collections:MIT Items

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