We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...
While supervised learning approaches for 3D shape retrieval have been successfully used to incorporate human knowledge about object classes based on global shape features, the inc...
Background subtraction algorithms define the background
as parts of a scene that are at rest. Traditionally,
these algorithms assume a stationary camera, and identify
moving obj...
Template-based object detectors such as the deformable parts model of Felzenszwalb et al. [11] achieve state-ofthe-art performance for a variety of object categories, but are stil...
Omkar M Parkhi, Andrea Vedaldi, C. V. Jawahar, And...
A novel method for extracting parametric junction and corner features in images is presented. By treating each complex feature as a combination of elementary line and edge feature...