Abstract
This paper proposes a novel object-Tracking method to estimate three dimensions position of texture-less objects using one camera system and 3D model. The system uses efficient chamfer matching method to calculated distances between 2D edge templates of pose hypotheses with edges from the Canny edge query image. Differential Evolution algorithm uses those distances as inputs to ensure the close optimum results and find the most suitable position of objects. For initialization the exhaustive searching is employed. With the good initialization, a smaller searching space is set to guaranty the online tracking ability. The first results showed the potential of the method in solving object tracking and detection problem.
| Original language | English |
|---|---|
| Article number | 15001 |
| Journal | MATEC Web of Conferences |
| Volume | 108 |
| DOIs | |
| Publication status | Published - 2017 May 31 |
Fingerprint
ASJC Scopus subject areas
- Chemistry(all)
- Engineering(all)
- Materials Science(all)
Cite this
Model-based pose estimation for texture-less objects with differential evolution algorithm. / Tao, Linh; Nguyen, Tinh; Hasegawa, Hiroshi.
In: MATEC Web of Conferences, Vol. 108, 15001, 31.05.2017.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Model-based pose estimation for texture-less objects with differential evolution algorithm
AU - Tao, Linh
AU - Nguyen, Tinh
AU - Hasegawa, Hiroshi
PY - 2017/5/31
Y1 - 2017/5/31
N2 - This paper proposes a novel object-Tracking method to estimate three dimensions position of texture-less objects using one camera system and 3D model. The system uses efficient chamfer matching method to calculated distances between 2D edge templates of pose hypotheses with edges from the Canny edge query image. Differential Evolution algorithm uses those distances as inputs to ensure the close optimum results and find the most suitable position of objects. For initialization the exhaustive searching is employed. With the good initialization, a smaller searching space is set to guaranty the online tracking ability. The first results showed the potential of the method in solving object tracking and detection problem.
AB - This paper proposes a novel object-Tracking method to estimate three dimensions position of texture-less objects using one camera system and 3D model. The system uses efficient chamfer matching method to calculated distances between 2D edge templates of pose hypotheses with edges from the Canny edge query image. Differential Evolution algorithm uses those distances as inputs to ensure the close optimum results and find the most suitable position of objects. For initialization the exhaustive searching is employed. With the good initialization, a smaller searching space is set to guaranty the online tracking ability. The first results showed the potential of the method in solving object tracking and detection problem.
UR - http://www.scopus.com/inward/record.url?scp=85020452828&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85020452828&partnerID=8YFLogxK
U2 - 10.1051/matecconf/201710815001
DO - 10.1051/matecconf/201710815001
M3 - Article
AN - SCOPUS:85020452828
VL - 108
JO - MATEC Web of Conferences
JF - MATEC Web of Conferences
SN - 2261-236X
M1 - 15001
ER -