International Journal of Computational Intelligence Systems

Volume 7, Issue 3, June 2014, Pages 506 - 514

Motion Key-frames extraction based on amplitude of distance characteristic curve

Authors
Qiang Zhang, Xiang Xue, Dongsheng Zhou, Xiaopeng Wei
Corresponding Author
Qiang Zhang
Received 14 July 2012, Accepted 15 December 2012, Available Online 1 June 2014.
DOI
https://doi.org/10.1080/18756891.2013.859873How to use a DOI?
Keywords
key-frames extraction, distance features, PCA, insert and merge, amplitude
Abstract
The key frames extraction technique extracts key postures to describe the original motion sequence, which has been widely used in motion compression, motion retrieval, motion edition and so on. In this paper, we propose a method based on the amplitude of curve to find key frames in a motion captured sequence. First we select a group of joint distance features to represent the motion and adopt the Principal Component Analysis (PCA) method to obtain the one dimension principal component as a features curve which will be used. Then we gain the initial key-frames by extracting the local optimum points in the curve. At last, we get the final key frames by inserting frames based on the amplitude of the curve and merging key frames too close. A number of experimental examples demonstrate that our method is practicable and efficient not only in the visual performance but also in the aspect of the compression ratio and error rate.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Journal
International Journal of Computational Intelligence Systems
Volume-Issue
7 - 3
Pages
506 - 514
Publication Date
2014/06
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
https://doi.org/10.1080/18756891.2013.859873How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - Qiang Zhang
AU  - Xiang Xue
AU  - Dongsheng Zhou
AU  - Xiaopeng Wei
PY  - 2014
DA  - 2014/06
TI  - Motion Key-frames extraction based on amplitude of distance characteristic curve
JO  - International Journal of Computational Intelligence Systems
SP  - 506
EP  - 514
VL  - 7
IS  - 3
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2013.859873
DO  - https://doi.org/10.1080/18756891.2013.859873
ID  - Zhang2014
ER  -