The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
— In this paper we propose a method of high-speed 3D object recognition using linear subspace method and our 3D features. This method can be applied to partial models with any si...
We present an implemented model for speech recognition in natural environments which relies on contextual information about salient entities to prime utterance recognition. The hyp...
Efficient detection of objects in images is complicated by variations of object appearance due to intra-class object differences, articulation, lighting, occlusions, and aspect va...
This paper presents a novel approach for labeling objects based on multiple spatially-registered images of a scene. We argue that such a multi-view labeling approach is a better fi...
Scott Helmer, David Meger, Marius Muja, James J. L...