This paper describes a method to localize 3D objects, which is the extension of the segment-based object recognition method to use on a STL CAD model. Models for localization are ...
This work proposes to learn visual encodings of attention patterns that enables sequential attention for object detection in real world environments. The system embeds a saccadic d...
Recognition of three dimensional (3D) objects in noisy and cluttered scenes is a challenging problem in 3D computer vision. One approach that has been successful in past research i...
Andrea Frome, Daniel Huber, Ravi Kolluri, Thomas B...
We present an irregular image pyramid which is derived from multi-scale analysis of segmented watershed regions. Our framework is based on the development of regions in the Gaussia...
The performance of supervised learners depends on the presence of a relatively large labeled sample. This paper proposes an automatic ongoing learning system, which is able to inco...