User Behavior Tracking for Education Assisting System by Using an RGB-D Sensor View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2019-11-07

AUTHORS

Haibin Xia , Bin Zhang , Tomoaki Nakamura , Takayuki Nagai , Takashi Omori , Masahide Kaneko , Rena Ushiogi , Natsuki Oka , Hun-ok Lim

ABSTRACT

It is difficult to track multiple people effectively for a long time in a complex environment because people’s clothes and body shapes may be similar, and their postures may be constantly changing. This paper proposes a novel method for multiple people tracking in crowded places where people can be partially or completely occluded. The people are detected by the deep learning method ConvNet from the color image first, and detection results are integrated with the depth information so that the accurate human areas can be extracted. The accurate personal color information can be extracted then without any background color information. multiple people tracking is proceeded by using particle filter based on the color information. the effectiveness of the proposed method is verified through experiments of tracking multiple children in a classroom. More... »

PAGES

923-931

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-030-32591-6_101

DOI

http://dx.doi.org/10.1007/978-3-030-32591-6_101

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1122361783


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