An approach of wavelet transform-based human pose models for indoor video applications

REFERENCES

• Horaud R, Niskanen M, Dewaele G, Boyer E. Human motion tracking by registering an articulated surface to 3D points and normals. IEEE Trans. Patt. Anal. Mach. Intell., 2009, 31, 158–164.
   PubMed Web of Science ®Google Scholar
• Aggarwal JK, Park S. Human motion: modelling and recognition of actions and interactions, Proc. 2nd Int. Symp. on 3D data processing, visualization, and transmission: 3DPVT 2004, Thessaloniki, Greece, September 2004, IEEE Computer Society, pp. 640–647.
   Google Scholar
• Orrite Urunuela C, del Rincon JM, Herrero Jaraba JE, Rogez G. 2D silhouette and 3D skeletal models for human detection and tracking, Proc. 17th Int. Conf. on Pattern recognition: ICPR 2004, Washington, DC, USA, August 2004, IEEE Computer Society, Vol. 4, pp. 244–247.
   Google Scholar
• Gupta A, Chen T, Chen F, Kimber D, Davis LS. Context and observation driven latent variable model for human pose estimation, Proc. IEEE Conf. on Computer vision and pattern recognition: CVPR 2008, Anchorage, AK, USA,June 2008, IEEE Computer Society, pp. 1–8.
   Google Scholar
• Apuzzo ND, Plaenkers R, Fua P. Least squares matching tracking algorithm for human body modelling. Int. Arch. Photogramm. Remote Sens., 2000, 33, 164–171.
   Google Scholar
• Ferrari V, Marin Jimenez M, Zisserman A. Progressive search space reduction for human pose estimation, Proc. IEEE Conf. on Computer vision and pattern recognition: CVPR 2008, Anchorage, AK, USA, June 2008, IEEE Computer Society, pp. 1–8.
   Google Scholar
• Porle RR, Hooi LS, Sainarayanan G. Human pose classification using neural network for visual surveillance, Proc. 3rd Int. Conf. on Artificial intelligence in engineering and technology: ICAIET 2006, Kota Kinabalu, Sabah, Malaysia, November 2006, University of Malaysia, pp. 33–43.
   Google Scholar
• Tesei A, Foresti GL, Regazzoni CS. Human body modelling for people localization and tracking from real image sequences, Proc. 5th Int. Conf. on Image processing and its applications: IPIA’95, Edinburgh, UK, July 1995, IEE, pp. 806–809.
   Google Scholar
• Porle R, Chekima A, Wong F, Sainarayanan G. Wavelet-based skin segmentation for detecting occluded arms in human body pose modelling system, Proc. Int. Conf. on Intelligent and advanced systems: ICIAS 2007, Kuala Lumpur, Malaysia, November 2007, CAS, pp. 764–769.
   Google Scholar
• Zhang XY, Zhao RC. Automatic image segmentation using wavelet transform and moving edge detection, Proc. 5th Int. Conf. on Machine learning and cybernetics: ICMLC 2006, Dalian, China, August 2006, IEEE Press, pp. 3929–3933.
   Google Scholar
• Zhang XP, Desai MD. Wavelet based automatic thresholding for image segmentation, Proc. 1st Int. Conf. on Image processing: ICIP’97, CA, Santa BarbaraUSA, October 1997, IEEE Computer Society, Vol. 1, pp. 224–228.
   Google Scholar
• Sateesh Kumar HC, Raja KB, Venugopal KR, Patnaik LM. Automatic image segmentation using wavelets. Int. J. Comput. Sci. Network Secur., 2009, 9, 305–313.
   Google Scholar
• Cheng FH, Chen YL. Real time multiple objects tracking and identification based on discrete wavelet transform. J. Patt. Recogn. Soc., 2006, 39, 1126–1139.
   Web of Science ®Google Scholar
• Werghi N, Xiao YJ. Wavelet moments for recognizing human body posture from 3D scans, Proc. 16th Int. Conf. on Pattern recognition: ICPR 2002, Quebec City, Que., Canada, August 2002, IEEE Computer Society, Vol. 1, pp. 319–322.
   Google Scholar
• Werghi W. A discriminative 3D wavelet-based descriptors: Application to the recognition of human body postures. Patt. Recogn. Lett., 2005, 26, 663–677.
   Web of Science ®Google Scholar
• Hahn BR, He L, Klette R. Automatic human model generation. Lect. Notes Comput. Sci., 2005, 2756, 41–48.
   Google Scholar
• Jaume i Capo A, Varona J, Hidalgo MG, Mas R, Perales FJ. Automatic human body modelling for vision-based motion capture, Proc. 14th Int. Conf. in Central Europe on Computer graphics, visualization and computer vision: WSCG 2006, Plzen, Czech Republic, January–February 2006, UNION Agency – Science Press pp. 1–6.
   Google Scholar
• Tian TP, Li R, Sclaroff S. ‘Tracking human body pose on a learned smooth space,’ Technical Report 2005-029, Boston University, Boston, MA, USA, 2005.
   Google Scholar
• Kakadiaris IA, Metaxas D. Model-based estimation of 3D human motion. IEEE Trans. Patt. Anal. Mach. Intell., 2000, 22, 1453–1459.
   Web of Science ®Google Scholar
• Howe NR, Leventon ME, Freeman WT. Bayesian reconstruction of 3D human motion from single camera video. Adv. Neural Inf. Process. Syst., 1999, 12, 820–826.
   Google Scholar
• Agarwal A, Triggs B. Recovering 3D human pose from monocular images. IEEE Trans. Patt. Anal. Mach. Intell., 2006, 28, 44–58.
   PubMed Web of Science ®Google Scholar
• Onishi K, Takiguchi T, Ariki Y. 3D human posture estimation using the HOG features from monocular image, Proc. 18th IEEE Int. Conf. on Pattern recognition: ICPR 2008, Tampa, FL, USA, December 2008, IEEE Computer Society, pp. 1–4.
   Google Scholar
• Wai LM, Cohen I. A model based approach for estimating human 3D poses in static images. Trans. Patt. Anal. Mach. Intell., 2006, 28, 905–916.
   PubMed Web of Science ®Google Scholar
• Hsieh JW, Hsu YT, Mark Liao HY, Chen CC. Video-based human movement analysis and its application to surveillance systems. IEEE Trans. Multimedia, 2008, 10, 372–384.
   Web of Science ®Google Scholar
• Ahanathapillai V, Soraghan JJ, Sonecki P. Delaunay triangulation based image enhancement for Echocardiography images, Proc. 17th European Signal Processing Conference: EUSIPCO-2009, Glasgow, UK, August 2009, EURASIP, pp. 1878–1882.
   Google Scholar
• Bern M, Eppstein D. In Computing in Euclidean Geometry, 1995, 2nd edition, pp. 47–123 (World Scientific, Singapore).
   Google Scholar
• Shewchuk J. Delaunay refinement algorithms for triangular mesh generation. Comput. Geom., 2002, 22, 21–74.
   Web of Science ®Google Scholar
• Chew LP. Constrained Delaunay triangulations. Algorithmica, 1989, 4, 97–108.
   Web of Science ®Google Scholar
• Horaud R, Niskanen M, Dewaele G, Boyer E. Human motion tracking by registering an articulated surface to 3D points and normals. IEEE Trans. Patt. Anal. Mach. Intell., 2009, 31, 158–163.
   PubMed Web of Science ®Google Scholar
• Zhao JH, Li L, Keong KC. In Computer Vision and Graphics (Ed. Wojciechowski et al.), 2006, pp. 1075–1081 (Springer, Dordrecht).
   Google Scholar
• Yan JY, Pollefeys M. A factorization based approach for articulated non-rigid shape, motion and kinematic chain recovery from video. IEEE Trans. Patt. Anal. Mach. Intell., 2008, 30, 865–877.
   PubMed Web of Science ®Google Scholar
• Gonzalez RC, Woods RE. Digital Image Processing, 2nd edition, 1992 (Pearson Education, Hong Kong).
   Google Scholar
• Tan P, Quan L, Shum HY. Highlight removal by illumination-constrained inpainting, Proc. 9th IEEE Int. Conf. on Computer vision: ICCV 2003, Nice, France, October 2003, IEEE Computer Society, pp. 164–169.
   Google Scholar
• Jayaraman S, Essakkirajan S, Veerakumar T. Digital Image Processing, 2009, 1st edition, pp. 619–623 (Tata McGraw Hill Education Ltd, New Delhi).
   Google Scholar