We propose an approach for detecting objects in large-scale range datasets that combines bottom-up and top-down processes. In the bottom-up stage, fast-to-compute local descriptors...
Alexander Patterson, Philippos Mordohai, Kostas Da...
This paper describes a new method of combining ray-casting with segmentation. Volume rendering is performed at interactive rates on standard laptop computers, and visualizations in...
In this paper we present a novel framework for generic object class detection by integrating Kernel PCA with AdaBoost. The classifier obtained in this way is invariant to changes...
The bounding box representation employed by many popular object detection models [3, 6] implicitly assumes all pixels inside the box belong to the object. This assumption makes th...
We present a novel framework for tracking of a long sequence of human activities, including the time instances of change from one activity to the next, using a closed-loop, non-li...