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?
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Castrillón-Santana, M., Vuong, Q.C. (2006). Combining Human Perception and Geometric Restrictions for Automatic Pedestrian Detection. In: Marín, R., Onaindía, E., Bugarín, A., Santos, J. (eds) Current Topics in Artificial Intelligence. CAEPIA 2005. Lecture Notes in Computer Science(), vol 4177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881216_18
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DOI: https://doi.org/10.1007/11881216_18
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