We present a tunable representation for tracking that simultaneously encodes appearance and geometry in a manner that enables the use of mean-shift iterations for tracking. The cl...
We consider a setting for discriminative semisupervised learning where unlabeled data are used with a generative model to learn effective feature representations for discriminativ...
Geometric reconstruction of the environment from images is critical in autonomous mapping and robot navigation. Geometric reconstruction involves feature tracking, i.e., locating ...
Feature selection is an important preprocessing step in pattern analysis and machine learning. The key issue in feature selection is to evaluate quality of candidate features. In t...
We present an activity recognition feature inspired by
human psychophysical performance. This feature is based
on the velocity history of tracked keypoints. We present a
generat...