Tracking multiple humans in complex situations

Tracking multiple humans in complex situations is challenging. The difficulties are tackled with appropriate knowledge in the form of various models in our approach. Human motion is decomposed into its global motion and limb motion. In the first part, we show how multiple human objects are segmented...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence. - 1979. - 26(2004), 9 vom: 15. Sept., Seite 1208-21
1. Verfasser: Zhao, Tao (VerfasserIn)
Weitere Verfasser: Nevatia, Ram
Format: Aufsatz
Sprache:English
Veröffentlicht: 2004
Zugriff auf das übergeordnete Werk:IEEE transactions on pattern analysis and machine intelligence
Schlagworte:Comparative Study Evaluation Study Journal Article Research Support, U.S. Gov't, Non-P.H.S.
LEADER 01000naa a22002652 4500
001 NLM153980532
003 DE-627
005 20231223065108.0
007 tu
008 231223s2004 xx ||||| 00| ||eng c
028 5 2 |a pubmed24n0513.xml 
035 |a (DE-627)NLM153980532 
035 |a (NLM)15742895 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Zhao, Tao  |e verfasserin  |4 aut 
245 1 0 |a Tracking multiple humans in complex situations 
264 1 |c 2004 
336 |a Text  |b txt  |2 rdacontent 
337 |a ohne Hilfsmittel zu benutzen  |b n  |2 rdamedia 
338 |a Band  |b nc  |2 rdacarrier 
500 |a Date Completed 31.03.2005 
500 |a Date Revised 10.12.2019 
500 |a published: Print 
500 |a Citation Status MEDLINE 
520 |a Tracking multiple humans in complex situations is challenging. The difficulties are tackled with appropriate knowledge in the form of various models in our approach. Human motion is decomposed into its global motion and limb motion. In the first part, we show how multiple human objects are segmented and their global motions are tracked in 3D using ellipsoid human shape models. Experiments show that it successfully applies to the cases where a small number of people move together, have occlusion, and cast shadow or reflection. In the second part, we estimate the modes (e.g., walking, running, standing) of the locomotion and 3D body postures by making inference in a prior locomotion model. Camera model and ground plane assumptions provide geometric constraints in both parts. Robust results are shown on some difficult sequences 
650 4 |a Comparative Study 
650 4 |a Evaluation Study 
650 4 |a Journal Article 
650 4 |a Research Support, U.S. Gov't, Non-P.H.S. 
700 1 |a Nevatia, Ram  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t IEEE transactions on pattern analysis and machine intelligence  |d 1979  |g 26(2004), 9 vom: 15. Sept., Seite 1208-21  |w (DE-627)NLM098212257  |x 1939-3539  |7 nnns 
773 1 8 |g volume:26  |g year:2004  |g number:9  |g day:15  |g month:09  |g pages:1208-21 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_350 
951 |a AR 
952 |d 26  |j 2004  |e 9  |b 15  |c 09  |h 1208-21