Learning Image Descriptors with the Boosting-Trick
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We present a fast method to detect humans from stationary surveillance videos. Traditional approaches exploit background subtraction as an attentive filter, by applying the still image detectors only on foreground regions. This doesn't take into account th ...
The ever increasing number of digital images in both public and private collections urges on the need for generic image content analysis systems. These systems need to be capable to capture the content of images from both scenes and objects, in a compact w ...
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The ever increasing number of digital images in both public and private collections urges on the need for generic image content analysis systems. These systems need to be capable to capture the content of images from both scenes and objects, in a compact w ...
We introduce a novel local image descriptor designed for dense wide-baseline matching purposes. We feed our descriptors to a graph-cuts based dense depth map estimation algorithm and this yields better wide-baseline performance than the commonly used corre ...
In this paper, we propose a fast algorithm for gesture recognition based on the saliency maps of visual attention. A tuned saliency-based model of visual attention is used to find potential hand regions in video frames. To obtain the overall movement of th ...
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In this paper, we present a fast method to detect humans from videos captured in surveillance applications. It is based on a cascade of LogitBoost classifiers relying on features mapped from the Riemanian manifold of region covariance matrices computed fro ...
We extend the standard boosting procedure to train a two-layer classifier dedicated to handwritten character recognition. The scheme we propose relies on a hidden layer which extracts feature vectors on a fixed number of points of interest, and an output l ...
Objective: To propose a new feature extraction method with canonical solution for multi-class Brain-Computer Interfaces (BCI). The proposed method should provide a reduced number of canonical discriminant spatial patterns (CDSP) and rank the channels sorte ...
