Title :
Pose recognition of giant pandas based on gradient shapes
Author :
Juan Chen ; Quan Wen ; Chenglong Zhuo ; Mete, Mutlu
Author_Institution :
Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Abstract :
In this paper, we proposed a novel approach towards the pose recognition of giant pandas based on the gradient shapes. The proposed approach is implemented in three main steps. First, the gradient contour is extracted by filtering the internal pixels in the gradient image. Second, a novel region partition method is used to measure the body weight of giant panda in different image directions. Third, the Fuzzy C-Means clustering is utilized to recognize various poses of giant panda based on the gradient shapes. Extensive experiments are carried out to validate the performance of the proposed method. The experimental results demonstrate that our method is quite promising.
Keywords :
feature extraction; filtering theory; fuzzy set theory; gradient methods; pattern clustering; performance evaluation; pose estimation; shape recognition; zoology; body weight measurement; fuzzy C-means clustering; giant panda; gradient contour extraction; gradient image; gradient shapes; image directions; internal pixel filtering; performance validation; pose recognition; region partition method; Face; Feature extraction; Filtering; Image edge detection; Shape; Vectors; Fuzzy C-Means; giant panda; gradient; pose recognition; shape features;
Conference_Titel :
Computational Problem-Solving (ICCP), 2012 International Conference on
Conference_Location :
Leshan
Print_ISBN :
978-1-4673-1696-5
Electronic_ISBN :
978-1-4673-1695-8
DOI :
10.1109/ICCPS.2012.6384309