CASIA OpenIR  > 智能感知与计算研究中心
Robust Object Recognition via Visual Pathway Feedback
Chong Wang; Junge Zhang; Peipei Yang; Kaiqi Huang
2014
会议名称International Conference on Pattern Recognition (ICPR)
会议录名称ICPR
会议日期2014
会议地点Stockholm,Sweden
摘要Object recognition, which consists of classification
and detection, has two important attributes for robustness: (1)

Closeness: detection windows should be close to object locations,
and (2)
Adaptiveness: object matching should be adaptive to
object variations in classification. It is difficult to satisfy both
attributes by considering classification and detection separately,
thus recent studies combine them based on confidence contextualization and foreground modeling. However, these combinations
neglect feature saliency and object structure, which are important
for recognition. In fact, object recognition originates in the
mechanism of “what” and “where” pathways in human visual
systems, and more importantly, these pathways have feedback to
each other, which provides a probable way to improve closeness
and adaptiveness. Inspired by the feedback, we propose a robust
object recognition framework by designing a computational
model of the feedback mechanism. In the “what” feedback, the
feature saliency from classification is exploited to rectify detection
windows for better closeness; while in the “where” feedback,
object parts from detection are used to model object matching of
object structure for better adaptiveness. Experiments show that
the “what” and “where” feedback can be effective to improve
closeness and adaptiveness for robust object recognition, and
encouraging results are obtained on the challenging PASCAL
VOC 2007 dataset

关键词Object Recognition Bag Of Words Visual Pathway Feedback
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/12430
专题智能感知与计算研究中心
通讯作者Kaiqi Huang
作者单位CASIA
推荐引用方式
GB/T 7714
Chong Wang,Junge Zhang,Peipei Yang,et al. Robust Object Recognition via Visual Pathway Feedback[C],2014.
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