Recent work shows how to use local spatio-temporal features to learn models of realistic human actions from video. However, existing methods typically rely on a predefined spatial...
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
We investigate how to discover all common visual patterns within two sets of feature points. Common visual patterns generally share similar local features as well as similar spati...
By combining Histograms of Oriented Gradients (HOG) and Local Binary Pattern (LBP) as the feature set, we propose a novel human detection approach capable of handling partial occl...
— Accurate localization of landmarks in the vicinity of a robot is a first step towards solving the SLAM problem. In this work, we propose algorithms to accurately estimate the ...