TY - CHAP
T1 - Temporal Factorization vs. Spatial Factorization
AU - Zelnik-Manor, Lihi
AU - Irani, Michal
PY - 2004
Y1 - 2004
N2 - The traditional subspace-based approaches to segmentation (often referred to as multi-body factorization approaches) provide spatial clustering/ segmentation by grouping together points moving with consistent motions. We are exploring a dual approach to factorization, i.e., obtaining temporal clustering/segmentation by grouping together frames capturing consistent shapes. Temporal cuts are thus detected at non-rigid changes in the shape of the scene/object. In addition it provides a clustering of the frames with consistent shape (but not necessarily same motion). For example, in a sequence showing a face which appears serious at some frames, and is smiling in other frames, all the "serious expression" frames will be grouped together and separated from all the "smile" frames which will be classified as a second group, even though the head may meanwhile undergo various random motions.
AB - The traditional subspace-based approaches to segmentation (often referred to as multi-body factorization approaches) provide spatial clustering/ segmentation by grouping together points moving with consistent motions. We are exploring a dual approach to factorization, i.e., obtaining temporal clustering/segmentation by grouping together frames capturing consistent shapes. Temporal cuts are thus detected at non-rigid changes in the shape of the scene/object. In addition it provides a clustering of the frames with consistent shape (but not necessarily same motion). For example, in a sequence showing a face which appears serious at some frames, and is smiling in other frames, all the "serious expression" frames will be grouped together and separated from all the "smile" frames which will be classified as a second group, even though the head may meanwhile undergo various random motions.
UR - http://www.scopus.com/inward/record.url?scp=35048820618&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-24671-8_34
DO - 10.1007/978-3-540-24671-8_34
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AN - SCOPUS:35048820618
SN - 3540219838
SN - 9783540219835
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 434
EP - 445
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
A2 - Pajdla, Tomáš
A2 - Matas, Jiří
ER -