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Modern search engines receive large numbers of business related, local aware queries. Such queries are best answered using accurate, up-to-date, business listings, that contain representations of business categories. Creating such listings is a challenging task as businesses often change hands or close down. For businesses with street side locations one can leverage the abundance of street level imagery,...
We address the problem of appearance-based person re-identification, which has been drawing an increasing amount of attention in computer vision. It is a very challenging task since the visual appearance of a person can change dramatically due to different backgrounds, camera characteristics, lighting conditions, view-points, and human poses. Among the recent studies on person re-id, color information...
Modeling objects using formal grammars has recently regained much attention in computer vision. Probabilistic logic programming, such as Bilattice based Logical Reasoning (BLR), is shown to produce impressive results in object detection/recognition. Although hierarchical object descriptions are preferred in high-level vision tasks for several reasons, BLR has been applied to non-hierarchical object...
Predicate logic based reasoning approaches provide a means of formally specifying domain knowledge and manipulating symbolic information to explicitly reason about different concepts of interest. Extension of traditional binary predicate logics with the bilattice formalism permits the handling of uncertainty in reasoning, thereby facilitating their application to computer vision problems. In this...
In forensic analysis of visual surveillance data, conditional knowledge representation and inference under uncertainty play an important role for deriving new contextual cues by fusing relevant evidential patterns. To address this aspect, both rule-based (aka. extensional) and state based (aka. intensional) approaches have been adopted for situation or visual event analysis. The former provides flexible...
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