We present a 3D matching framework based on a many-to-many matching algorithm that works with skeletal representations of 3D volumetric objects. We demonstrate the performance of ...
Nicu D. Cornea, M. Fatih Demirci, Deborah Silver, ...
Dense stereo algorithms rely on matching over a range of disparities. To speed up the search and reduce match ambiguity, processing can be embedded in the hierarchical, or coarse-...
Matching Pursuit decomposes a signal into a linear expansion of functions selected from a redundant dictionary, isolating the signal structures that are coherent with respect to a...
Fulvio Moschetti, Lorenzo Granai, Pierre Vanderghe...
We propose a structured approach to the problem of retrieval of images by content and present a description logic that has been devised for the semantic indexing and retrieval of ...
Eugenio Di Sciascio, Francesco M. Donini, Marina M...
We propose a new Bayesian approach to object-based image retrieval with relevance feedback. Although estimating the object posterior probability density from few examples seems in...
Derek Hoiem, Rahul Sukthankar, Henry Schneiderman,...