|Title:||Combining human perception and geometric restrictions for automatic pedestrian detection||Authors:||Castrillón-Santana, M.
Vuong, Quoc C.
|UNESCO Clasification:||120304 Inteligencia artificial||Keywords:||Head Tracking||Issue Date:||2006||Journal:||Lecture Notes in Computer Science||Conference:||11th Conference of the Spanish-Association-for-Artificial-Intelligence
11th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2005
|Abstract:||Automatic detection systems do not perform as well as human observers, even on simple detection tasks. A potential solution to this problem is training vision systems on appropriate regions of interests (ROIs), in contrast to training on predefined and arbitrarily selected regions. Here we focus on detecting pedestrians in static scenes. Our aim is to answer the following question: Can automatic vision systems for pedestrian detection be improved by training them on perceptually-defined ROIs?||URI:||http://hdl.handle.net/10553/17531||ISBN:||3-540-45914-6
|ISSN:||0302-9743||DOI:||10.1007/11881216_18">||Source:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)[ISSN 0302-9743],v. 4177 LNAI, p. 163-170|
|Appears in Collections:||Actas de congresos|
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