Evaluation of color spatio-temporal interest points for human action recognition

This paper considers the recognition of realistic human actions in videos based on spatio-temporal interest points (STIPs). Existing STIP-based action recognition approaches operate on intensity representations of the image data. Because of this, these approaches are sensitive to disturbing photomet...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 23(2014), 4 vom: 01. Apr., Seite 1569-80
1. Verfasser: Everts, Ivo (VerfasserIn)
Weitere Verfasser: van Gemert, Jan C, Gevers, Theo
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2014
Zugriff auf das übergeordnete Werk:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Schlagworte:Journal Article
LEADER 01000naa a22002652 4500
001 NLM235921793
003 DE-627
005 20231224104435.0
007 cr uuu---uuuuu
008 231224s2014 xx |||||o 00| ||eng c
024 7 |a 10.1109/TIP.2014.2302677  |2 doi 
028 5 2 |a pubmed24n0786.xml 
035 |a (DE-627)NLM235921793 
035 |a (NLM)24577192 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Everts, Ivo  |e verfasserin  |4 aut 
245 1 0 |a Evaluation of color spatio-temporal interest points for human action recognition 
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 03.12.2014 
500 |a Date Revised 28.02.2014 
500 |a published: Print 
500 |a Citation Status MEDLINE 
520 |a This paper considers the recognition of realistic human actions in videos based on spatio-temporal interest points (STIPs). Existing STIP-based action recognition approaches operate on intensity representations of the image data. Because of this, these approaches are sensitive to disturbing photometric phenomena, such as shadows and highlights. In addition, valuable information is neglected by discarding chromaticity from the photometric representation. These issues are addressed by color STIPs. Color STIPs are multichannel reformulations of STIP detectors and descriptors, for which we consider a number of chromatic and invariant representations derived from the opponent color space. Color STIPs are shown to outperform their intensity-based counterparts on the challenging UCF sports, UCF11 and UCF50 action recognition benchmarks by more than 5% on average, where most of the gain is due to the multichannel descriptors. In addition, the results show that color STIPs are currently the single best low-level feature choice for STIP-based approaches to human action recognition 
650 4 |a Journal Article 
700 1 |a van Gemert, Jan C  |e verfasserin  |4 aut 
700 1 |a Gevers, Theo  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society  |d 1992  |g 23(2014), 4 vom: 01. Apr., Seite 1569-80  |w (DE-627)NLM09821456X  |x 1941-0042  |7 nnns 
773 1 8 |g volume:23  |g year:2014  |g number:4  |g day:01  |g month:04  |g pages:1569-80 
856 4 0 |u http://dx.doi.org/10.1109/TIP.2014.2302677  |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 23  |j 2014  |e 4  |b 01  |c 04  |h 1569-80