Abstract
Detecting the regions of the various scene elements is a well-known computer vision and image processing problem called segmentation. Scene segmentation has traditionally been approached by way of (single) images
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References
O. Arif,W. Daley, P.A. Vela, J. Teizer, and J. Stewart. Visual tracking and segmentation using time-of-flight sensor. In Image Processing (ICIP), 2010 17th IEEE International Conference on, pages 2241 –2244, sept. 2010.
A. Bleiweiss and M.Werman. Fusing time-of-flight depth and color for real-time segmentation and tracking. In Proceedings of DAGM 2009 Workshop on Dynamic 3D Imaging, pages 58–69, 2009.
Y. Boykov, O. Veksler, and R. Zabih. Fast approximate energy minimization via graph cuts.IEEE Transactions on Pattern Analysis and Machine Intelligence, 23:1222–1239, 2001.
F. Calderero and F. Marques. Hierarchical fusion of color and depth information at partition level by cooperative region merging. In Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing ICASSP 2009, pages 973–976, 2009.
Y. Cheng. Mean shift, mode seeking, and clustering. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 17(8):790 –799, aug 1995.
Y. Y. Chuang, B. Curless, D. H. Salesin, and R. Szeliski. A bayesian approach to digital matting. Computer Vision and Pattern Recognition, IEEE Computer Society Conference on, 2:264, 2001.
Recommendations on uniform color spaces, color difference equations, psychometric color terms. Supplement No.2 to CIE publication No. 15 (E.-1.3.1) 1971/(TC-1.3.), 1978.
D. Comaniciu and P. Meer. Mean shift: a robust approach toward feature space analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002.
R. Crabb, C. Tracey, A. Puranik, and J. Davis. Real-time foreground segmentation via range and color imaging. In Computer Vision and Pattern Recognition Workshops, 2008. CVPRW ’08. IEEE Computer Society Conference on, pages 1 –5, june 2008.
Dal Mutto C, Zanuttigh P, Cortelazzo GM, Scene segmentation assisted by stereo vision. In Proceedings of 3DIMPVT, (2011) Hangzhou. China, May, 2011
B. Dellen, G. Aleny´a, S. Foix, and C. Torras. Segmenting color images into surface patches by exploiting sparse depth data. In Proc. of Winter Vision Meeting: Workshop on Applications of Computer Vision, pages 591–598, 2011.
P.F. Felzenszwalb and D.P. Huttenlocher. Efficient graph-based image segmentation. International Journal of Computer Vision, 2004.
D. Holz, S. Holzer, R. Bogdan Rusu, and S. Behnke. Real-time plane segmentation using rgbd cameras. In Proceedings of the 15th RoboCup International Symposium, Istanbul, Turkey, July 2011.
V. Kolmogorov, A. Criminisi, A. Blake, G. Cross, and C. Rother. Bi-layer segmentation of binocular stereo video. In Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, volume 2, page 1186 vol. 2, june 2005.
L. Ladicky, P. Sturgess, C. Russell, S. Sengupta, Y. Bastanlar, W. Clocksin, and P. Torr. Joint optimisation for object class segmentation and dense stereo reconstruction. volume BMVC special award issue, pages 1–12, 2011.
J. Leens, S. Pirard, O. Barnich, M. Van Droogenbroeck, and J.-M. Wagner. Combining color depth, and motion for video segmentation. In ICVS’09, pages 104–113, 2009.
Pal NR, Pal SK (1993) A review on image segmentation techniques. Pattern Recognition 26(9):1277–1294
T. Porter and T. Duff. Compositing digital images. In Proceedings of the 11th annual conference on Computer graphics and interactive techniques, SIGGRAPH ’84, pages 253–259, New York, NY, USA, 1984. ACM.
T. Rabbani, F. Van Den Heuvel, and G. Vosselmann. Segmentation of point clouds using smoothness constraint. In International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, volume 36, Dresden, Germany, September 2006.
Schnabel R, Wahl R, Klein R (2007) Efficient ransac for point-cloud shape detection. Computer Graphics Forum 26(2):214–226
J. Shi and J. Malik. Normalized cuts and image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000.
Sun J, Jia J, Tang C, Shum H (August 2004) Poisson matting ACM Trans Graph 23:315–321
Szeliski R (2010) Computer Vision: Algorithms and Applications. Springer, New York
M. Wallenberg, M. Felsberg, P. Forssen, and B. Dellen. Channel coding for joint colour and depth segmentation. In Lecture Notes in Computer Science (Proceedings of the 33rd Annual Symposium of the German Association for Pattern Recognition), volume 6835, pages 306–315. Springer, 2011.
L. Wang, M. Gong, C. Zhang, R. Yang, C. Zhang, and Y.-H. Yang. Automatic real-time video matting using time-of-flight camera and multichannel poisson equations. International Journal of Computer Vision, pages 1–18, 2011.
Wang L, Zhang C, Yang R, Zhang C,Tofcut: Towards robust real-time foreground extraction using time-of-flight camera. In Proceedings of 3DPVT, (2010) Paris. France, May, 2010
O. Wang, J. Finger, Q. Yang, J. Davis, and R. Yang. Automatic natural video matting with depth. In Computer Graphics and Applications, 2007. PG ’07. 15th Pacific Conference on, pages 469 –472, nov. 2007.
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Mutto, C.D., Zanuttigh, P., Cortelazzo, G.M. (2012). Scene Segmentation and Video Matting Assisted by Depth Data. In: Time-of-Flight Cameras and Microsoft Kinect™. SpringerBriefs in Electrical and Computer Engineering(). Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-3807-6_6
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DOI: https://doi.org/10.1007/978-1-4614-3807-6_6
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