caa a22 4500 605469865 CHVBK 20210128100324.0 cr unu---uuuuu 210128e20150401xx s 000 0 eng 10.1007/s00500-014-1410-x doi (NATIONALLICENCE)springer-10.1007/s00500-014-1410-x Overlapped latent Dirichlet allocation for efficient image segmentation [Elektronische Daten] [Young-Seob Jeong, Ho-Jin Choi] Unsupervised methods for image segmentation have recently drawn significant attention because most images do not have labels or tags. A topic model is an unsupervised probabilistic method that captures the latent aspects of data, where each latent aspect or topic is associated with one homogeneous region. In this paper, we propose a new topic model for image segmentation task that incorporates spatial information into its structure based on the hypothesis that overlapped topic proportions convey spatial information. The model is efficient in time and memory, and we demonstrate this through comparison with other models using the MSRC image dataset. Springer-Verlag Berlin Heidelberg, 2014 Probabilistic topic model nationallicence Image segmentation nationallicence Spatial information nationallicence Jeong Young-Seob Department of Computer Science, KAIST, 291 Daehak-ro, Yuseong-gu, 305-701, Daejeon, South Korea aut Choi Ho-Jin Department of Computer Science, KAIST, 291 Daehak-ro, Yuseong-gu, 305-701, Daejeon, South Korea aut Soft Computing Springer Berlin Heidelberg 19/4(2015-04-01), 829-838 1432-7643 19:4<829 2015 19 500 https://doi.org/10.1007/s00500-014-1410-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1410-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Jeong Young-Seob Department of Computer Science, KAIST, 291 Daehak-ro, Yuseong-gu, 305-701, Daejeon, South Korea aut NATIONALLICENCE 700 1- Choi Ho-Jin Department of Computer Science, KAIST, 291 Daehak-ro, Yuseong-gu, 305-701, Daejeon, South Korea aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/4(2015-04-01), 829-838 1432-7643 19:4<829 2015 19 500