تشخیص اجزای بدن انسان در تصاویر RGB-D با استفاده از ویژگی-های الگوی تغییرات عمق و تفاضل مکانی عمق

[1] محمد امین نعمت‌اللهی, سید علی اکبر صفوی, محمد علی حاج‌عباسی, محمد رحیم همتیان, «حل سینماتیک وارون روبات‌های فرافزونه‌ای با استفاده از شبکه عصبی موجکی»، مجله مهندسی برق دانشگاه تبریز, دوره40، شماره 1، صفحه­ی 57-68، 1389.

[2] رسول قربانی، حمید ابریشمی مقدم, «استفاده از بینای استریو به منظور ارائه یک سامانه واقعیت افزوده مبتنی بر بینایی»،  مجله مهندسی برق دانشگاه تبریز, دوره 45، شماره 1، صفحه­ی 1-11، 1392.­

[3]      J. Shotton, A. Fitzgibbon, M. Cook, T. Sharp, M. Finocchio, R. Moore, A. Kipman and A. Blake, “Real-time human pose recognition in parts from a single depth image”, Communications of the ACM, vol. 56 pp. 116–124, 2011.

[4]      L. He, G Wang, Q. Liao and J.  Xue, “Depth-images-based pose estimation using regression forests and graphical models” Neurocomputing, vol.164, pp. 210-219, 2015.

[5]      L. Breiman. “Random forests”, Machine learning, vol. 45, pp. 5-32, 2001.

[6]      http://mocap.cs.cmu.edu/ ,December 10, 2017

[7]      L. Vincent, P. Lagger and P. Fua. “Randomized trees for real-time keypoint recognition”, Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on. Vol. 2, pp. 775-781, 2005.

[8]      L. Hui, J. Yuan, and D. Thalmann. “Parsing the hand in depth images”, IEEE Transactions on Multimedia vol. 16, pp. 1241-1253, 2014.

[9]      K. Buys,C. Cagniart.,A. Baksheev,T. De Laet,J. De Schutter and C. Pantofaru, “An adaptable system for RGB-D based human body detection and pose estimation”, Journal of visual communication and image representation, vol. 25. pp. 39-52, 2014.

[10]      R. Girshick, J. Shotton, P. Kohli, A. Criminisi and A. Fitzgibbon, “Efficient regression of general-activity human poses from depth images”, Computer Vision (ICCV), 2011 IEEE International Conference on. IEEE, pp. 415-422, 2011.

[11]      B. Leibe, A. Leonardis and B. Schiele. “Robust object detection with interleaved categorization and segmentation”, International journal of computer vision, vol. 77, pp. 259–289, 2008.

[12]      J. Gall and V. Lempitsky, “Class-specific Hough forests for object detection”, Decision forests for computer vision and medical image analysis. pp, 143-157, 2009.

[13]      S. Min, P. Kohli and J. Shotton. “Conditional regression forests for human pose estimation”, Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on. IEEE, pp. 3394-3401, 2012.

[14]      C. Ju Yong, S. Woo Nam. “Fast Random-Forest-Based Human Pose Estimation Using a Multi-scale and Cascade Approach”, ETRI Journal, vol. 35, pp. 949-959, 2013.

[15]      T. Daniel, H. Liang and J. Yuan, “First-Person Palm Pose Tracking and Gesture Recognition in Augmented Reality”, International Joint Conference on Computer Vision, Imaging and Computer Graphics, pp. 3-15, 2015.

[16]      Y.Jung, H. Lee, S. Heo and Y. Dong Yun, “Random tree walk toward instantaneous 3D human pose estimation”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2467-2474, 2015.

[17]      W. Xiaolin, P. Zhang and J. Chai, “Accurate realtime full-body motion capture using a single depth camera”, ACM Transactions on Graphics, vol. 31 188, 2012.

[18]      J. Ahmad, Y. Kim and D. Kim. “Ridge body parts features for human pose estimation and recognition from RGB-D video data”, Computing, Communication and Networking Technologies (ICCCNT), 2014 International Conference on. IEEE, pp. 1-6, 2014.

[19]      E. Brian, G. Dunn. “Principal components analysis”, Applied Multivariate Data Analysis, Second Edition, pp. 48-73, 1993.

[20]      L. Yazhou, P. Lasang, M. Siegel and Q. Sun. “Geodesic invariant feature: A local descriptor in depth”, IEEE Transactions on Image Processing, vol. 24, pp. 236-248, 2015.

[21]      S. Schwarz, L. Arthur, A. Mkhitaryan, D. Mateus and  N. Navab, “Human skeleton tracking from depth data using geodesic distances and optical flow” , Image and Vision Computing , vol. 30 , pp. 217-226 , 2012.

[22]      C. Plagemann, V. Ganapathi, D. Koller and S. Thrun, “Real-time identification and localization of body parts from depth images”, Robotics and Automation (ICRA), 2010 IEEE International Conference on. IEEE, pp. 3108-3113, 2010.

[23]      J. M.,C. Wolf, G. Taylor and A. Baskurt, “Human body part estimation from depth images via spatially-constrained deep learning ”, Pattern Recognition Letters ,vol. 50 pp. 122-129, 2014.

[24]      A. Shafaei, J. James, “Real-Time Human Motion Capture with Multiple Depth Cameras”, Computer and Robot Vision (CRV), 2016 13th Conference on. IEEE, pp.24-31, 2016.

[25]      http://www.makehuman.org/, December 10, 2017.

[26]      https://www.blender.org/, December 10, 2017.

[27]      https://www.autodesk.com/products/motionbuilder/overview, December 10, 2017.

[28]      https://www.autodesk.com/products/3ds-max/overview, December 10, 2017)