|
|
|
|
| LEADER |
01000naa a22002652 4500 |
| 001 |
NLM252590686 |
| 003 |
DE-627 |
| 005 |
20231224164432.0 |
| 007 |
cr uuu---uuuuu |
| 008 |
231224s2014 xx |||||o 00| ||eng c |
| 024 |
7 |
|
|a 10.1109/TPAMI.2013.239
|2 doi
|
| 028 |
5 |
2 |
|a pubmed24n0842.xml
|
| 035 |
|
|
|a (DE-627)NLM252590686
|
| 035 |
|
|
|a (NLM)26353192
|
| 040 |
|
|
|a DE-627
|b ger
|c DE-627
|e rakwb
|
| 041 |
|
|
|a eng
|
| 100 |
1 |
|
|a Haines, Tom S F
|e verfasserin
|4 aut
|
| 245 |
1 |
0 |
|a Background Subtraction with DirichletProcess Mixture Models
|
| 264 |
|
1 |
|c 2014
|
| 336 |
|
|
|a Text
|b txt
|2 rdacontent
|
| 337 |
|
|
|a ƒaComputermedien
|b c
|2 rdamedia
|
| 338 |
|
|
|a ƒa Online-Ressource
|b cr
|2 rdacarrier
|
| 500 |
|
|
|a Date Completed 27.11.2015
|
| 500 |
|
|
|a Date Revised 10.09.2015
|
| 500 |
|
|
|a published: Print
|
| 500 |
|
|
|a Citation Status PubMed-not-MEDLINE
|
| 520 |
|
|
|a Video analysis often begins with background subtraction. This problem is often approached in two steps-a background model followed by a regularisation scheme. A model of the background allows it to be distinguished on a per-pixel basis from the foreground, whilst the regularisation combines information from adjacent pixels. We present a new method based on Dirichlet process Gaussian mixture models, which are used to estimate per-pixel background distributions. It is followed by probabilistic regularisation. Using a non-parametric Bayesian method allows per-pixel mode counts to be automatically inferred, avoiding over-/under- fitting. We also develop novel model learning algorithms for continuous update of the model in a principled fashion as the scene changes. These key advantages enable us to outperform the state-of-the-art alternatives on four benchmarks
|
| 650 |
|
4 |
|a Journal Article
|
| 650 |
|
4 |
|a Research Support, Non-U.S. Gov't
|
| 700 |
1 |
|
|a Tao Xiang
|e verfasserin
|4 aut
|
| 773 |
0 |
8 |
|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 36(2014), 4 vom: 01. Apr., Seite 670-83
|w (DE-627)NLM098212257
|x 1939-3539
|7 nnns
|
| 773 |
1 |
8 |
|g volume:36
|g year:2014
|g number:4
|g day:01
|g month:04
|g pages:670-83
|
| 856 |
4 |
0 |
|u http://dx.doi.org/10.1109/TPAMI.2013.239
|3 Volltext
|
| 912 |
|
|
|a GBV_USEFLAG_A
|
| 912 |
|
|
|a SYSFLAG_A
|
| 912 |
|
|
|a GBV_NLM
|
| 912 |
|
|
|a GBV_ILN_350
|
| 951 |
|
|
|a AR
|
| 952 |
|
|
|d 36
|j 2014
|e 4
|b 01
|c 04
|h 670-83
|