INFORMATION CHANGE THE WORLD

International Journal of Information Technology and Computer Science(IJITCS)

ISSN: 2074-9007 (Print), ISSN: 2074-9015 (Online)

Published By: MECS Press

IJITCS Vol.10, No.11, Nov. 2018

Color Based New Algorithm for Detection and Single/Multiple Person Face Tracking in Different Background Video Sequence

Full Text (PDF, 946KB), PP.39-48


Views:16   Downloads:0

Author(s)

Ranganatha S, Y P Gowramma

Index Terms

Detection;Face tracking;Different background;Video sequence;YCbCr color;Eigen features;Point tracker

Abstract

Due to the lack of particular algorithms for automatic detection and tracking of person face(s), we have developed a new algorithm to achieve detection and single/multiple face tracking in different background video sequence. To detect faces, skin sections are segmented from the frame by means of YCbCr color model; and facial features are used to agree whether these sections contain person face or not. This procedure is challenging, because face color is unique and some objects may have similar color. Further, color and Eigen features are extracted from detected faces. Based on the points detected in facial region, point tracker tracks the user specified number of faces throughout the video sequence. The developed algorithm was tested on challenging dataset videos; and measured for performance using standard metrics. Test results obtained ensure the efficiency of proposed algorithm at the end.

Cite This Paper

Ranganatha S, Y P Gowramma, "Color Based New Algorithm for Detection and Single/Multiple Person Face Tracking in Different Background Video Sequence", International Journal of Information Technology and Computer Science(IJITCS), Vol.10, No.11, pp.39-48, 2018. DOI: 10.5815/ijitcs.2018.11.04

Reference

[1]Ranganatha S and Dr. Y P Gowramma, “Face Recognition Techniques: A Survey”, International Journal for Research in Applied Science and Engineering Technology (IJRASET), ISSN: 2321-9653, Vol.3, No.4, pp.630-635, April 2015.

[2]P. Viola and M. Jones, “Robust Real-Time Face Detection”, International Journal of Computer Vision (IJCV), Vol.57, pp.137-154, 2004.

[3]P. Viola and M. Jones, “Rapid Object Detection Using a Boosted Cascade of Simple Features”, in Proc. of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Kauai, USA, Vol.1, pp.511-518, December 2001. DOI: 10.1109/CVPR.2001.990517

[4]N. Dalal and B. Triggs, “Histograms of Oriented Gradients for Human Detection”, in Proc. of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Vol.1, pp.886-893, June 2005. DOI: 10.1109/CVPR.2005.177 

[5]David G. Lowe, “Distinctive Image Features from Scale-Invariant Keypoints”, International Journal of Computer Vision (IJCV), Vol.60, No.2, pp.91-110, November 2004.

[6]J. Wu and J. M. Rehg, “CENTRIST: A Visual Descriptor for Scene Categorization”, in IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), Vol.33, No.8, pp.1489-1501, August 2011. DOI: 10.1109/TPAMI.2010.224.

[7]Jianbo Shi and Carlo Tomasi, “Good Features to Track”, in Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.593-600, June 1994. DOI: 10.1109/CVPR.1994.323794

[8]Prashanth Kumar G and Shashidhara M, “Real Time Detection and Tracking of Human Face using Skin Color Segmentation and Region Properties”, International Journal of Image, Graphics and Signal Processing (IJIGSP), Vol.6, No.8, pp.40-46, July 2014. DOI: 10.5815/ijigsp.2014.08.06

[9]Ranganatha S and Y P Gowramma, “Development of Robust Multiple Face Tracking Algorithm and Novel Performance Evaluation Metrics for Different Background Video Sequences”, International Journal of Intelligent Systems and Applications (IJISA), Vol.10, No.8, pp.19-35, August 2018. DOI: 10.5815/ijisa.2018.08.03

[10]Mohammad Saber Iraji and Azam Tosinia, “Skin Color Segmentation in YCBCR Color Space with Adaptive Fuzzy Neural Network (Anfis)”, International Journal of Image, Graphics and Signal Processing (IJIGSP), Vol.4, No.4, pp.35-41, May 2012. DOI: 10.5815/ijigsp.2012.04.05

[11]K. Fukunaga and L. D. Hostetler, “The Estimation of the Gradient of a Density Function, with Applications in Pattern Recognition”, in IEEE Trans. on Information Theory, Vol.21, No.1, pp.32-40, January 1975. DOI: 10.1109/TIT.1975.1055330

[12]Yizong Cheng, “Mean Shift, Mode Seeking, and Clustering”, in IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), Vol.17, No.8, pp.790-799, August 1995. DOI: 10.1109/34.400568

[13]G. Bradski, “Computer Vision Face Tracking for Use in a Perceptual User Interface”, Intel Technology Journal, pp.12-21, 1998.

[14]Chunbo Xiu, Xuemiao Su, and Xiaonan Pan, “Improved Target Tracking Algorithm based on Camshift”, in Proc. of IEEE Chinese Control and Decision Conference (CCDC), pp.4449-4454, June 2018. DOI: 10.1109/CCDC.2018.8407900

[15]Bruce D. Lucas and Takeo Kanade, “An Iterative Image Registration Technique with an Application to Stereo Vision”, in Proc. of International Joint Conference on Artificial Intelligence, Vol.2, pp.674-679, August 1981.

[16]Carlo Tomasi and Takeo Kanade, “Detection and Tracking of Point Features”, Carnegie Mellon University Technical Report CMU-CS-91-132, April 1991.

[17]Ranganatha S and Y P Gowramma, “A Novel Fused Algorithm for Human Face Tracking in Video Sequences”, in Proc. of IEEE International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS), pp.1-6, October 2016. DOI: 10.1109/CSITSS.2016.7779430

[18]C. Harris and M. Stephens, “A Combined Corner and Edge Detector”, in Proc. of 4th Alvey Vision Conference, Manchester, UK, pp.147-151, 1988.

[19]Ranganatha S and Y P Gowramma, “An Integrated Robust Approach for Fast Face Tracking in Noisy Real-World Videos with Visual Constraints”, in Proc. of IEEE International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp.772-776, September 2017. DOI: 10.1109/ICACCI.2017.8125935

[20]J. Strom, T. Jebara, S. Basu, and A. Pentland, “Real Time Tracking and Modeling of Faces: An EKF-based Analysis by Synthesis Approach”, in Proc. of IEEE International Workshop on Modelling People (MPeople), pp.55-61, September 1999. DOI: 10.1109/PEOPLE.1999.798346

[21]Douglas Decarlo and Dimitris N. Metaxas, “Optical Flow Constraints on Deformable Models with Applications to Face Tracking”, International Journal of Computer Vision (IJCV), Vol.38, No.2, pp.99-127, July 2000.

[22]Natalia Chaudhry and Kh. M. Umar Suleman, “IP Camera Based Video Surveillance Using Object’s Boundary Specification”, International Journal of Information Technology and Computer Science (IJITCS), Vol.8, No.8, pp.13-22, August 2016. DOI: 10.5815/ijitcs.2016.08.02 

[23]M. Kim, S. Kumar, V. Pavlovic, and H. Rowley, “Face Tracking and Recognition with Visual Constraints in Real-World Videos”, in Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.1-8, June 2008. DOI: 10.1109/CVPR.2008.4587572

[24]Ranganatha S and Y P Gowramma, “Image Training and LBPH Based Algorithm for Face Tracking in Different Background Video Sequence”, International Journal of Computer Sciences and Engineering (IJCSE), Vol.6, No.9, September 2018. 

[25]Ranganatha S and Y P Gowramma, “Image Training, Corner and FAST Features based Algorithm for Face Tracking in Low Resolution Different Background Challenging Video Sequences”, International Journal of Image, Graphics and Signal Processing (IJIGSP), Vol.10, No.8, pp.39-53, August 2018. DOI: 10.5815/ijigsp.2018.08.05 

[26]Stefan Leutenegger, Margarita Chli, and Roland Y. Siegwart, “BRISK: Binary Robust Invariant Scalable Keypoints”, in Proc. of IEEE International Conference on Computer Vision (ICCV), pp.2548-2555, November 2011. DOI: 10.1109/ICCV.2011.6126542

[27]Md. Abdur Rahim, Md. Najmul Hossain, Tanzillah Wahid, and Md. Shafiul Azam, “Face Recognition using Local Binary Patterns (LBP)”, Global Journal of Computer Science and Technology, Vol.13, No.4, pp.1-8, 2013.

[28]E. Rosten and T. Drummond, “Fusing Points and Lines for High Performance Tracking”, in Proc. of IEEE International Conference on Computer Vision (ICCV), Vol.2, pp.1508-1515, October 2005. DOI: 10.1109/ICCV.2005.104

[29]Ranganatha S and Y P Gowramma, “Selected Single Face Tracking in Technically Challenging Different Background Video Sequences Using Combined Features”, ICTACT Journal on Image and Video Processing (JIVP), in press.

[30]D. M. W. Powers, “Evaluation: From Precision, Recall and F-Measure to ROC, Informedness, Markedness & Correlation”, Journal of Machine Learning Technologies (JMLT), Vol.2, No.1, pp.37-63, 2011.

[31]T. Fawcett, “An Introduction to ROC Analysis”, Pattern Recognition Letters, Vol.27, No.8, pp.861-874, June 2006. DOI: 10.1016/j.patrec.2005.10.010

[32]Keni Bernardin and Rainer Stiefelhagen, “Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics”, EURASIP Journal on Image and Video Processing, pp.1-10, May 2008. DOI: 10.1155/2008/246309