Pedestrian Detection via Classification on Riemannian Manifolds
We present a new algorithm to detect pedestrian in still images utilizing covariance matrices as object descriptors. Since the descriptors do not form a vector space, well known machine learning techniques are not well suited to learn the classifiers. The space of d-dimensional nonsingular covariance matrices can be represented as a connected Riemannian manifold. The main contribution of the paper is a novel approach for classifying points lying on a connected Riemannian manifold using the...[Show more]
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|Source:||IEEE Transactions on Pattern Analysis and Machine Intelligence|
|01_Tuzel_Pedestrian_Detection_via_2008.pdf||700.7 kB||Adobe PDF||Request a copy|
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