Real-Time Human Tracker Based on Location and Motion Recognition of User for Smart Home 


Vol. 16,  No. 3, pp. 209-216, Jun.  2009
10.3745/KIPSTA.2009.16.3.209


PDF
  Abstract

The ubiquitous smart home is the home of the future that takes advantage of context information from the human and the home environment and provides an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. We present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. We used four network cameras for real-time human tracking. This paper explains the real-time human tracker's architecture, and presents an algorithm with the details of two functions (prediction of human location and motion) in the real-time human tracker. The human location uses three kinds of background images (IMAGE1: empty room image, IMAGE2: image with furniture and home appliances in the home, IMAGE3: image with IMAGE2 and the human). The real-time human tracker decides whether the human is included with which furniture (or home appliance) through an analysis of three images, and predicts human motion using a support vector machine. A performance experiment of the human's location, which uses three images, took an average of 0.037 seconds. The SVM's feature of human's motion recognition is decided from pixel number by array line of the moving object. We evaluated each motion 1000 times. The average accuracy of all the motions was found to be 86.5.

  Statistics
  Cite this article

[IEEE Style]

J. H. Choi, S. Y. Park, D. K. Shin, D. I. Shin, "Real-Time Human Tracker Based on Location and Motion Recognition of User for Smart Home," The KIPS Transactions:PartA, vol. 16, no. 3, pp. 209-216, 2009. DOI: 10.3745/KIPSTA.2009.16.3.209.

[ACM Style]

Jong Hwa Choi, Se Young Park, Dong Kyoo Shin, and Dong Il Shin. 2009. Real-Time Human Tracker Based on Location and Motion Recognition of User for Smart Home. The KIPS Transactions:PartA, 16, 3, (2009), 209-216. DOI: 10.3745/KIPSTA.2009.16.3.209.

Forms

Search
(IN TITLE, AUTHOR, ABSTRACT,KEYWORDS)

Advanced Search ▼

POPULAR KEYWORDS
(TOP 10 KEYWORDS)

Recent Publications
(LAST 3 YEARS)

Old Journals

Indexing

All publications of TKIPS is indexed in DOI, EBSCO, Google Scholar, Crossref, and CrossCheck.

TKIPS is also selected as the Journal for Accreditation by NRF (National Research Foundation of Korea).

Related Journals