Combining human perception and geometric restrictions for automatic pedestrian detection
Data(s) |
21/06/2016
21/06/2016
2005
|
---|---|
Resumo |
<p>[EN]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?</p> |
Identificador |
http://hdl.handle.net/10553/17531 725932 <p><a href="http://dx.doi.org/10.1007/11881216_18" target="_blank">10.1007/11881216_18</a></p> |
Idioma(s) |
eng |
Direitos |
info:eu-repo/semantics/openAccess |
Fonte |
<p>Current Topics in Artificial Intelligence. Berlin: Springer, 2006 (Lecture Notes in Computer Science, ISSN 0302-9743; vol. 4177; pp 163-170). ISBN 978-3-540-45914-9. ISBN online 978-3-540-45915-6</p> |
Palavras-Chave | #120304 Inteligencia artificial |
Tipo |
info:eu-repo/semantics/conferenceObject |