Literature DB >> 15742895

Tracking multiple humans in complex situations.

Tao Zhao1, Ram Nevatia.   

Abstract

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.

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Year:  2004        PMID: 15742895     DOI: 10.1109/TPAMI.2004.73

Source DB:  PubMed          Journal:  IEEE Trans Pattern Anal Mach Intell        ISSN: 0098-5589            Impact factor:   6.226


  2 in total

1.  Using an improved SIFT algorithm and fuzzy closed-loop control strategy for object recognition in cluttered scenes.

Authors:  Haitao Nie; Kehui Long; Jun Ma; Dan Yue; Jinguo Liu
Journal:  PLoS One       Date:  2015-02-25       Impact factor: 3.240

2.  Process mining for individualized behavior modeling using wireless tracking in nursing homes.

Authors:  Carlos Fernández-Llatas; José-Miguel Benedi; Juan M García-Gómez; Vicente Traver
Journal:  Sensors (Basel)       Date:  2013-11-11       Impact factor: 3.576

  2 in total

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