CVPR
2007
IEEE
15 years 5 days ago
2007
IEEE
This paper describes a patch-based approach for rapid image correlation or template matching. By representing a template image with an ensemble of patches, the method is robust wi...
CVPR
2007
IEEE
15 years 5 days ago
2007
IEEE
We study retinal curvature estimation from multiple images that provides the fundamental geometry of human retina. We use an affine camera model due to its simplicity, linearity, ...
CVPR
2007
IEEE
15 years 5 days ago
2007
IEEE
Object detection can be challenging when the object class exhibits large variations. One commonly-used strategy is to first partition the space of possible object variations and t...
CVPR
2007
IEEE
15 years 5 days ago
2007
IEEE
Being the most broadly used tool for deceit measurement, the polygraph is a limited method as it suffers from human operator subjectivity and the fact that target subjects are awa...
CVPR
2007
IEEE
15 years 5 days ago
2007
IEEE
We present an object class detection approach which fully integrates the complementary strengths offered by shape matchers. Like an object detector, it can learn class models dire...
CVPR
2007
IEEE
2007
IEEE
Leveraging temporal, contextual and ordering constraints for recognizing complex activities in video
15 years 5 days ago
We present a scalable approach to recognizing and describing complex activities in video sequences. We are interested in long-term, sequential activities that may have several par...
CVPR
2007
IEEE
15 years 5 days ago
2007
IEEE
Belief propagation over pairwise connected Markov Random Fields has become a widely used approach, and has been successfully applied to several important computer vision problems....
CVPR
2007
IEEE
15 years 5 days ago
2007
IEEE
CVPR
2007
IEEE
15 years 5 days ago
2007
IEEE
It is well-known that forward motion induces a large number of local minima in the instantaneous least-squares reprojection error. This is caused in part by singularities in the e...
CVPR
2007
IEEE
15 years 5 days ago
2007
IEEE
Dimensionality reduction is an important issue when facing high-dimensional data. For supervised dimensionality reduction, Linear Discriminant Analysis (LDA) is one of the most po...