Abstract
This paper proposes an efficient algorithm for head pose tracking. The most preexisting head pose tracking method usually consists of high cost computing algorithm. Therefore, it is difficult to implement head pose tracking in a mobile system with low performance hardware such as smartphone. In this paper, we propose a low cost computing algorithm for fast head pose tracking method. The proposed method consists of two stages: rough tracking and precise tracking stages. Especially, this paper discusses the efficient design of precise tracking stage. According to the experimental results, we demonstrate that our method increases the tracking performance using the proposed coarse-to-fine random sampling algorithm.
Original language | English |
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Title of host publication | Proceedings of the SICE Annual Conference |
Pages | 2513-2517 |
Number of pages | 5 |
Publication status | Published - 2013 |
Event | 2013 52nd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2013 - Nagoya, Japan Duration: 2013 Sep 14 → 2013 Sep 17 |
Other
Other | 2013 52nd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2013 |
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Country | Japan |
City | Nagoya |
Period | 13/9/14 → 13/9/17 |
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Keywords
- Coarse-to-fine random sampling
- Head pose tracking
- Image processing
- Measurement
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Computer Science Applications
Cite this
Head pose tracking based on optimizing normalized cross-correlation. / Takahashi, Koichi; Mitsukura, Yasue.
Proceedings of the SICE Annual Conference. 2013. p. 2513-2517.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Head pose tracking based on optimizing normalized cross-correlation
AU - Takahashi, Koichi
AU - Mitsukura, Yasue
PY - 2013
Y1 - 2013
N2 - This paper proposes an efficient algorithm for head pose tracking. The most preexisting head pose tracking method usually consists of high cost computing algorithm. Therefore, it is difficult to implement head pose tracking in a mobile system with low performance hardware such as smartphone. In this paper, we propose a low cost computing algorithm for fast head pose tracking method. The proposed method consists of two stages: rough tracking and precise tracking stages. Especially, this paper discusses the efficient design of precise tracking stage. According to the experimental results, we demonstrate that our method increases the tracking performance using the proposed coarse-to-fine random sampling algorithm.
AB - This paper proposes an efficient algorithm for head pose tracking. The most preexisting head pose tracking method usually consists of high cost computing algorithm. Therefore, it is difficult to implement head pose tracking in a mobile system with low performance hardware such as smartphone. In this paper, we propose a low cost computing algorithm for fast head pose tracking method. The proposed method consists of two stages: rough tracking and precise tracking stages. Especially, this paper discusses the efficient design of precise tracking stage. According to the experimental results, we demonstrate that our method increases the tracking performance using the proposed coarse-to-fine random sampling algorithm.
KW - Coarse-to-fine random sampling
KW - Head pose tracking
KW - Image processing
KW - Measurement
UR - http://www.scopus.com/inward/record.url?scp=84888595517&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84888595517&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84888595517
SP - 2513
EP - 2517
BT - Proceedings of the SICE Annual Conference
ER -