Learning topic of dynamic scene using belief propagation and weighted visual words approach
| LEADER | caa a22 4500 | ||
|---|---|---|---|
| 001 | 605468427 | ||
| 003 | CHVBK | ||
| 005 | 20210128100316.0 | ||
| 007 | cr unu---uuuuu | ||
| 008 | 210128e20150101xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s00500-014-1384-8 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s00500-014-1384-8 | ||
| 245 | 0 | 0 | |a Learning topic of dynamic scene using belief propagation and weighted visual words approach |h [Elektronische Daten] |c [Chunping Liu, Hui Lin, Shengrong Gong, Yi ji, Quan Liu] |
| 520 | 3 | |a In this paper, we are tackling the problem of distinguishing scenes, including static and dynamic scenes. We propose a framework of scene recognition, based on bag of visual words and topic model. We achieve the task using the topic model by belief propagation (TMBP), which belongs to the family of the latent Dirichlet allocation model. We also extend the TMBP model, called as the knowledge TMBP model, by introducing the prior information of visual words and scenes. Experimental results on the static and dynamic scenes demonstrated that our proposed framework is effective and efficient. The scene semantics can be obtained from two levels of visual words and topics in our framework. Our result significantly outperforms the others using low-level visual features, such as spatial, temporal and spatiotemporal features. | |
| 540 | |a Springer-Verlag Berlin Heidelberg, 2014 | ||
| 690 | 7 | |a Scene recognition |2 nationallicence | |
| 690 | 7 | |a Topic model |2 nationallicence | |
| 690 | 7 | |a Bag of visual words |2 nationallicence | |
| 690 | 7 | |a Topic model by belief propagation (TMBP) |2 nationallicence | |
| 700 | 1 | |a Liu |D Chunping |u School of Computer Science and Technology, Soochow University, 215006, Suzhou, China |4 aut | |
| 700 | 1 | |a Lin |D Hui |u School of Computer Science and Technology, Soochow University, 215006, Suzhou, China |4 aut | |
| 700 | 1 | |a Gong |D Shengrong |u School of Computer Science and Technology, Soochow University, 215006, Suzhou, China |4 aut | |
| 700 | 1 | |a ji |D Yi |u School of Computer Science and Technology, Soochow University, 215006, Suzhou, China |4 aut | |
| 700 | 1 | |a Liu |D Quan |u School of Computer Science and Technology, Soochow University, 215006, Suzhou, China |4 aut | |
| 773 | 0 | |t Soft Computing |d Springer Berlin Heidelberg |g 19/1(2015-01-01), 71-84 |x 1432-7643 |q 19:1<71 |1 2015 |2 19 |o 500 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s00500-014-1384-8 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s00500-014-1384-8 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Liu |D Chunping |u School of Computer Science and Technology, Soochow University, 215006, Suzhou, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Lin |D Hui |u School of Computer Science and Technology, Soochow University, 215006, Suzhou, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Gong |D Shengrong |u School of Computer Science and Technology, Soochow University, 215006, Suzhou, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a ji |D Yi |u School of Computer Science and Technology, Soochow University, 215006, Suzhou, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Liu |D Quan |u School of Computer Science and Technology, Soochow University, 215006, Suzhou, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Soft Computing |d Springer Berlin Heidelberg |g 19/1(2015-01-01), 71-84 |x 1432-7643 |q 19:1<71 |1 2015 |2 19 |o 500 | ||