This paper presents a 3D approach to multi-view object class detection. Most existing approaches recognize object classes for a particular viewpoint or combine classifiers for a f...
This paper addresses the issue of unsupervised network anomaly detection. In recent years, networks have played more and more critical roles. Since their outages cause serious eco...
We present an information theoretic approach for learning a linear dimension reduction transform for object classification. The theoretic guidance of the approach is that the trans...
We describe a novel method for human detection in single images which can detect full bodies as well as close-up views in the presence of clutter and occlusion. Humans are modeled ...
Krystian Mikolajczyk, Cordelia Schmid, Andrew Ziss...
We investigate the problem of pedestrian detection in
still images. Sliding window classifiers, notably using the
Histogram-of-Gradient (HOG) features proposed by Dalal
and Trig...