We develop hierarchical, probabilistic models for objects, the parts composing them, and the visual scenes surrounding them. Our approach couples topic models originally developed...
Erik B. Sudderth, Antonio Torralba, William T. Fre...
Linear decompressors are the dominant methodology used in commercial test data compression tools. However, they are generally not able to exploit correlations in the test data, an...
This paper summarizes a probabilistic approach for localizing people through the signal strengths of a wireless IEEE 802.11b network. Our approach uses data labeled by ground trut...
Sebastian Thrun, Geoffrey J. Gordon, Frank Pfennin...
We introduce a robust probabilistic approach to modeling shape contours based on a lowdimensional, nonlinear latent variable model. In contrast to existing techniques that use obj...
Labeling video data is an essential prerequisite for many vision applications that depend on training data, such as visual information retrieval, object recognition, and human act...