Object detection and tracking has various application areas including intelligent transportation systems. We introduce an object detection and tracking approach that combines the ...
We propose a new integrated approach based on Markov logic networks (MLNs), an effective combination of probabilistic graphical models and firstorder logic for statistical relatio...
Recently, in generic object recognition research, a classification technique based on integration of image features is garnering much attention. However, with a classifying techn...
We combine local texture features (PCA-SIFT), global features (shape context), and spatial features within a single multi-layer AdaBoost model of object class recognition. The fir...
Wei Zhang 0002, Bing Yu, Gregory J. Zelinsky, Dimi...
We present a probabilistic framework for component-based automatic detection and tracking of objects in video. We represent objects as spatio-temporal two-layer graphical models, w...
Leonid Sigal, Ying Zhu, Dorin Comaniciu, Michael J...