No Access

VIDEO IMAGE CLUSTERING BASED ON HUMAN FACE AND SHIRT COLOR

MD. SHAFAEAT HOSSAIN

Department of Computer Science and Engineering, University of Dhaka, Dhaka-1000, Bangladesh

Search for more papers by this author

KHANDAKER ABIR RAHMAN

Department of Computer Science and Engineering, University of Dhaka, Dhaka-1000, Bangladesh

Search for more papers by this author

MD. HASANUZZAMAN

Department of Computer Science and Engineering, University of Dhaka, Dhaka-1000, Bangladesh

Search for more papers by this author

M. A. BHUYIAN

Department of Computer Science and Engineering, Jahangirnagar University, Savar, Bangladesh

Search for more papers by this author

, and

H. UENO

National Institute of Informatics (NII), Tokyo, Japan

Search for more papers by this author

https://doi.org/10.1142/S0219467810003639Cited by:2 (Source: Crossref)

Abstract

This paper proposes a novel video image clustering method based on human face and shirt color. Clustering has been performed in unsupervised manner where no prior knowledge about the input video clip is required. For face detection, multi-resolution templates based pattern matching method has been used. We have experimented on 11 video clips of various durations in order to evaluate the performance of the proposed system. The ability of the system to generate a meaningful number of clusters that exist in the input video clip is definitely well. The performance of the system with respect to precision and recall rate is also highly satisfactory.

Keywords:

Remember to check out the Check out our Most Cited Articles!
Check out these titles on Image Analysis

References

M. Flickneret al., IEEE Computer 23 (1995). Google Scholar
H. J. Zhanget al., Pattern Recognition 30(4), 643 (1997), DOI: 10.1016/S0031-3203(96)00109-4. Crossref, Web of Science, Google Scholar
K. Barnard, P. Duygulu and D. Forsyth, Clustering art, Proc. of the 2001 IEEE Computer Society Conference Computer Vision and Pattern Recognition 2001, CVPR2 (2001) pp. II-434–II-441. Google Scholar
K. Barnard and D. Forsyth, Learning the semantics of words and pictures, Proc. of International Conference on Computer Vision2 (2001) pp. 408–415. Google Scholar
S. Eickeler et al. , Content based indexing of images and video using face detection and recognition methods , Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing ( 2001 ) . Google Scholar
Csaba Czirjek et al. , Face detection and clustering for video indexing applications , ACIVS 2003 — Advanced Concepts for Intelligent Vision Systems ( 2003 ) . Google Scholar
J. E. Viallet and O. Bernier, Face detection for video summaries, Proc. of CIVR'20022383 (Springer, Berlin/Heidelberg, 2002) pp. 95–147. Google Scholar
E. Acostaet al., An automatic face detection and recognition system for video indexing applications, Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing4 (2002) pp. IV-3644–IV-3647. Google Scholar
M. H. Yang, D. J. Kriegman and N. Ahuja, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 24(1), 34 (2002). Crossref, Web of Science, Google Scholar
M. Hasanuzzamanet al., Real-time Vision-based Gesture Recognition for Human-Robot Interaction, Proc. of IEEE International Conference on Robotics and Biomimetics (ROBIO'2004) (2004) pp. 379–384. Google Scholar
J. Miaoet al., Pattern Recognition 32(7), 1237 (1999), DOI: 10.1016/S0031-3203(98)00156-3. Crossref, Web of Science, Google Scholar
C. W. Park and M. Park, Journal of Applied Sciences 6(4), 795 (2006). Crossref, Web of Science, Google Scholar
J. Yanget al., Visual tracking for multimodal human computer interaction, Proc. of ACM CHI'98 Human Factors in Computing Systems (1998) pp. 140–147. Google Scholar
T. Darrelet al., International Journal of Computer Vision 37(2), 175 (2000), DOI: 10.1023/A:1008103604354. Crossref, Web of Science, Google Scholar
H. M. El-Bakry, International Journal of Intelligent Systems and Technologies 1, (2006). Google Scholar
A. Hamdy, M. Elmahdy and M. Elsabrouty, Face detection using PCA and skin-tone extraction for drowsy driver application, Proc. of ITI 5th International Conference on Information and Communications Technology (2007) pp. 135–137. Google Scholar
C. M. Taskiranet al., Detection of unique people in news programs using multimodal shot clustering, Proc. of International Conference on Image Processing1 (2004) pp. 697–700. Google Scholar
J. B. MacQueen, Some Methods for classification and Analysis of Multivariate Observations, Proc. of 5th Berkeley Symposium on Mathematical Statistics and Probability (University of California Press, 1967) pp. 281–297. Google Scholar
H. Steinhaus, Bull. Acad. Polon. Sci. 4(12), 801 (1956). Google Scholar
M. Inaba, N. Katoh and H. Imai, Applications of weighted Voronoi diagrams and randomization to variance-based K-clustering, Proc. of 10th ACM Symposium on Computational Geometry (1994) pp. 332–339. Google Scholar
B. Malinga , D. Raicu and J. Furst , Local versus Global histogram-based color image clustering , CTI Research Symposium ( 2006 ) . Google Scholar