We describe a hierarchical probabilistic model for the detection and recognition of objects in cluttered, natural scenes. The model is based on a set of parts which describe the e...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
This paper presents a new method of detecting and predicting motion tracking failures with applications in human motion and gait analysis. We define a tracking failure as an event...
Shiloh L. Dockstader, Nikita S. Imennov, A. Murat ...
Principal component analysis (PCA) is a powerful fault detection and isolation method. However, the classical PCA which is based on the estimation of the sample mean and covariance...
We propose a new approach for detecting low textured
planar objects and estimating their 3D pose. Standard
matching and pose estimation techniques often depend on
texture and fe...
Stefan Holzer, Stefan Hinterstoisser, Slobodan Ili...
Information Extraction (IE) is the task of extracting knowledge from unstructured text. We present a novel unsupervised approach for information extraction based on graph mutual r...