TY - GEN
T1 - Sparse coding of linear dynamical systems with an application to dynamic texture recognition
AU - Ghanem, Bernard
AU - Ahuja, Narendra
PY - 2010
Y1 - 2010
N2 - Given a sequence of observable features of a linear dynamical system (LDS), we propose the problem of finding a representation of the LDS which is sparse in terms of a given dictionary of LDSs. Since LDSs do not belong to Euclidean space, traditional sparse coding techniques do not apply. We propose a probabilistic framework and an efficient MAP algorithm to learn this sparse code. Since dynamic textures (DTs) can be modeled as LDSs, we validate our framework and algorithm by applying them to the problems of DT representation and DT recognition. In the case of occlusion, we show that this sparse coding scheme outperforms conventional DT recognition methods.
AB - Given a sequence of observable features of a linear dynamical system (LDS), we propose the problem of finding a representation of the LDS which is sparse in terms of a given dictionary of LDSs. Since LDSs do not belong to Euclidean space, traditional sparse coding techniques do not apply. We propose a probabilistic framework and an efficient MAP algorithm to learn this sparse code. Since dynamic textures (DTs) can be modeled as LDSs, we validate our framework and algorithm by applying them to the problems of DT representation and DT recognition. In the case of occlusion, we show that this sparse coding scheme outperforms conventional DT recognition methods.
UR - http://www.scopus.com/inward/record.url?scp=78149476550&partnerID=8YFLogxK
U2 - 10.1109/ICPR.2010.247
DO - 10.1109/ICPR.2010.247
M3 - Conference contribution
AN - SCOPUS:78149476550
SN - 9780769541099
T3 - Proceedings - International Conference on Pattern Recognition
SP - 987
EP - 990
BT - Proceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010
T2 - 2010 20th International Conference on Pattern Recognition, ICPR 2010
Y2 - 23 August 2010 through 26 August 2010
ER -