TY - GEN
T1 - A GPU-accelerated particle filter with pixel-level likelihood
AU - Lenz, Claus
AU - Panin, Giorgio
AU - Knoll, Alois
PY - 2008
Y1 - 2008
N2 - We present in this paper a GPU-accelerated particle filter based on pixel-level segmentation and matching, for real-time object tracking. The proposed method achieves real-time perfomance, while computing for each particle the corresponding filled model silhouette through the rendering engine of the graphics card, and comparing it with the underlying binary map of the segmentation preprocess. With the proposed approach, a better precision and generality is obtained with respect to related feature-level likelihoods such as color histograms, while keeping low computational requirements.
AB - We present in this paper a GPU-accelerated particle filter based on pixel-level segmentation and matching, for real-time object tracking. The proposed method achieves real-time perfomance, while computing for each particle the corresponding filled model silhouette through the rendering engine of the graphics card, and comparing it with the underlying binary map of the segmentation preprocess. With the proposed approach, a better precision and generality is obtained with respect to related feature-level likelihoods such as color histograms, while keeping low computational requirements.
UR - http://www.scopus.com/inward/record.url?scp=84881568378&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84881568378
SN - 9781586039219
T3 - 13th International Fall Workshop Vision, Modeling, and Visualization 2008, VMV 2008
SP - 235
EP - 241
BT - 13th International Fall Workshop Vision, Modeling, and Visualization 2008, VMV 2008
T2 - 13th International Fall Workshop Vision, Modeling, and Visualization 2008, VMV 2008
Y2 - 8 October 2008 through 10 October 2008
ER -