Unsupervised learning can be used to extract image representations that are useful for various and diverse vision tasks. After noticing that most biological vision systems for int...
This paper proposes a model-based methodology for recognizing and tracking objects in digital image sequences. Objects are represented by attributed relational graphs (or ARGs), w...
Ana Beatriz V. Graciano, Roberto Marcondes Cesar J...
The problem of pose estimation arises in many areas of computer vision, including object recognition, object tracking, site inspection and updating, and autonomous navigation when...
Philip David, Daniel DeMenthon, Ramani Duraiswami,...
We present an object recognition system that locates an object, identifies its parts, and segments out its contours. A key distinction of our approach is that we use long, salien...
Recently, psychological studies showed that averaging human face images greatly improves the performance of face recognition under various pose, illumination, expression, and/or a...