New techniques are described for model-based recognition of the objects in 3-D space. The recognition is performed from single gray-scale images taken from unknown viewpoints. The objects in the scene may be overlapping and partially occluded. An efficient matching algorithm, which assumes affine approximation to the prospective viewing transformation, is proposed. The algorithm has an offline model preprocessing (shape representation) phase which is independent of the scene information and a recognition phase based on efficient indexing. It has a straightforward parallel implementation. The algorithm was successfully tested in recognition of industrial objects appearing in composite occluded scenes.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Image deformations due to relative motion between an observer and an object may be used to infer 3-D structure. Up to the first order, these deformations can be written in terms...
An object recognition system has been developed that uses a new class of local image features. The features are invariant to image scaling, translation, and rotation, and partia...
The Hausdorff distance measures the extent to which each point of a model set lies near some point of an image set and vice versa. Thus, this distance can be used to determine t...
We present an unsupervised technique for visual learning which is based on density estimation in high-dimensional spaces using an eigenspace decomposition. Two types of density ...
A stereo vision system that attempts to achieve robustness with respect to scene characteristics, from textured outdoor scenes to environments composed of highly regular man-mad...
Social media, news, blog, policy document mentions