This paper presents a method for finding and classifying objects within real-world scenes by using the activity of humans interacting with these objects to infer the object’s i...
Patrick Peursum, Svetha Venkatesh, Geoff A. W. Wes...
This chapter proposes a representation of rigid three-dimensional (3D) objects in terms of local affine-invariant descriptors of their images and the spatial relationships between ...
Fred Rothganger, Svetlana Lazebnik, Cordelia Schmi...
In this paper we introduce a formalism for optimal camera parameter selection for iterative state estimation. We consider a framework based on Shannon’s information theory and se...
Joachim Denzler, Christopher M. Brown, Heinrich Ni...
Adapting the classifier trained on a source domain to recognize instances from a new target domain is an important problem that is receiving recent attention. In this paper, we p...
We use the color cooccurrence histogram (CH) for recognizing objects in images. The color CH keeps track of the number of pairs of certain colored pixels that occur at certain sep...