A survey on high coherence visual media retargeting: recent advances and applications

doi:10.1007/s11704-016-6084-3

Front. Comput. Sci.

2016, Vol. 10

Issue (5) : 778-796 https://doi.org/10.1007/s11704-016-6084-3

REVIEW ARTICLE

A survey on high coherence visual media retargeting: recent advances and applications

Weimin TAN,Bo YAN(

)

School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing, Fudan University, Shanghai 201203, China

Download: PDF(983 KB)
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

The numerous works on media retargeting call for a thorough and comprehensive survey for reviewing and categorizing existing works and providing insights that can help future design of retargeting approaches and its applications. First, we present the basic problem of media retargeting and detail state-of-the-art retargeting methods devised to solve it. Second, we review recent works on objective quality assessment of media retargeting, where we find that although these works are designed to make the objective assessment result in accordance with the subjective evaluation, they are only suitable for certain situations. Considering the subjective nature of aesthetics, designing objective assessment metric for media retargeting could be a promising area for investigation. Third, we elaborate on other applications extended from retargeting techniques. We show how to apply the retargeting techniques in other fields to solve their challenging problems, and reveal that retargeting technique is not just a simple scaling algorithm, but a thought or concept, which has great flexibility and is quite useful.We believe this review can help researchers and practitioners to solve the existing problems of media retargeting and bring new ideas in their works.

Keywords media retargeting quality assessment aesthetenhancement image retrieval video synopsis

Corresponding Author(s): Bo YAN

Just Accepted Date: 16 May 2016 Online First Date: 18 July 2016 Issue Date: 07 September 2016

Cite this article:

Weimin TAN,Bo YAN. A survey on high coherence visual media retargeting: recent advances and applications[J]. Front. Comput. Sci., 2016, 10(5): 778-796.

URL:

https://academic.hep.com.cn/fcs/EN/10.1007/s11704-016-6084-3
https://academic.hep.com.cn/fcs/EN/Y2016/V10/I5/778

1	Grundmann M, Kwatra V, Han M, Essa I. Discontinuous seam-carving for video retargeting. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2010, 569–576 https://doi.org/10.1109/cvpr.2010.5540165
2	Avidan S, Shamir A. Seam carving for content-aware image resizing. ACM Transactions on Graphics (TOG), 2007, 26(3): 10 https://doi.org/10.1145/1276377.1276390
3	Panozzo D, Weber O, Sorkine O. Robust image retargeting via axisaligned deformation. Computer Graphics Forum, 2012, 31(2pt1): 229–236 https://doi.org/10.1111/j.1467-8659.2012.03001.x
4	Wang Y S, Tai C L, Sorkine O, Lee T Y. Optimized scale-and-stretch for image resizing. ACM Transactions on Graphics (TOG), 2008, 27(5): 118 https://doi.org/10.1145/1409060.1409071
5	Yan B, Li K, Yang X C, Hu T X. Seam searching based pixel fusion for image retargeting. IEEE Transactions on Circuits and Systems for Video Technology, 2015, 25(1): 15–23 https://doi.org/10.1109/TCSVT.2014.2329374
6	Fang Y M, Chen Z Z, Lin W S, Lin C W. Saliency-based image retargeting in the compressed domain. In: Proceedings of the 19th ACM international conference on Multimedia. 2011, 1049–1052 https://doi.org/10.1145/2072298.2071935
7	Mansfield A, Gehler P, Van Gool L, Rother C. Scene carving: scene consistent image retargeting. In: Daniilidis K, Maragos P, Paragios N, eds. Computer Vision–ECCV 2010. Springer Berlin Heidelberg, 2010, 143–156 https://doi.org/10.1007/978-3-642-15549-9_11
8	Qi S Y, Ho J. Seam segment carving: retargeting images to irregularlyshaped image domains. In: Fitzgibbon A, Lazebnik S, Perona P, et al, eds. Computer Vision–ECCV 2012, Springer Berlin Heidelberg, 2012, 314–326 https://doi.org/10.1007/978-3-642-33783-3_23
9	Shen J B, Wang D P, Li X L. Depth-aware image seam carving. IEEE Transactions on Cybernetics, 2013, 43(5): 1453–1461 https://doi.org/10.1109/TCYB.2013.2273270
10	Noh H, Han B. Seam carving with forward gradient difference maps. In: Proceedings of the 20th ACM international conference on Multimedia. 2012, 709–712 https://doi.org/10.1145/2393347.2396293
11	Battiato S, Farinella G M, Puglisi G, Ravi D. Saliency-based selection of gradient vector flow paths for content aware image resizing. IEEE Transactions on Image Processing, 2014, 23(5): 2081–2095 https://doi.org/10.1109/TIP.2014.2312649
12	Dong W M, Zhou N, Lee T Y, Wu F Z, Kong Y, Zhang X P. Summarization-based image resizing by intelligent object carving. IEEE Transactions on Visualization and Computer Graphics, 2014,20(1): 1 https://doi.org/10.1109/TVCG.2013.103
13	Santella A, Agrawala M, DeCarlo D, Salesin D, Cohen M. Gaze-based interaction for semi-automatic photo cropping. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 2006, 771–780 https://doi.org/10.1145/1124772.1124886
14	Zhang L M, Wang M, Nie L Q, Hong L, Rui Y, Tian Q. Retargeting semantically-rich photos. IEEE Transactions on Multimedia (TMM), 2015, 17(9): 1538–1549 https://doi.org/10.1109/TMM.2015.2451954
15	Chang C H, Chuang Y Y. A line-structure-preserving approach to image resizing. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2012, 1075–1082 https://doi.org/10.1109/cvpr.2012.6247786
16	Lin S S, Yeh I C, Lin C H, Lee T Y. Patch-based image warping for content-aware retargeting. IEEE Transactions on Multimedia (TMM), 2013, 15(2): 359–368 https://doi.org/10.1109/TMM.2012.2228475
17	Felzenszwalb P F, Huttenlocher D P. Efficient graph-based image segmentation. International Journal of Computer Vision, 2004, 59(2): 167–181 https://doi.org/10.1023/B:VISI.0000022288.19776.77
18	Wu Y C, Liu X T, Liu S X, Ma K L. ViSizer: a visualization resizing framework. IEEE Transactions on Visualization and Computer Graphics, 2013, 19(2): 278–290 https://doi.org/10.1109/TVCG.2012.114
19	Gallea R, Ardizzone E, Pirrone R. Physical metaphor for streaming media retargeting. IEEE Transactions on Multimedia, 2014, 16(4): 971–979 https://doi.org/10.1109/TMM.2014.2305917
20	Yan B, Yang X C, Li K. Efficient image retargeting via adaptive pixel fusion. In: Proceedings of the 22nd ACM International Conference on Multimedia. 2014, 929–932 https://doi.org/10.1145/2647868.2654959
21	Rubinstein M, Shamir A, Avidan S. Multi-operator media retargeting. ACM Transactions on Graphics, 2009, 28(3): 23 https://doi.org/10.1145/1531326.1531329
22	Dong W M, Zhou N, Paul J C, Zhang X P. Optimized image resizing using seam carving and scaling. ACM Transactions on Graphics, 2009, 28(5): 125 https://doi.org/10.1145/1618452.1618471
23	Liu Z, Yan H B, L. Shen L Q, Ngan K N, Zhang Z Y. Adaptive image retargeting using saliency-based continuous seam carving. Optical Engineering, 2010, 49(1)
24	Zhang G X, Cheng M M, Hu S M, Martin R R. A shape-preserving approach to image resizing. Computer Graphics Forum, 2009, 28(7): 1897–1906 https://doi.org/10.1111/j.1467-8659.2009.01568.x
25	Liu Y, Sun L F, Yang S Q. A retargeting method for stereoscopic 3D video. Computational Visual Media, 2015, 1(2): 119–127 https://doi.org/10.1007/s41095-015-0016-2
26	Dong W M, Wu F Z, Kong Y, Mei X, Lee T Y, Zhang X P. Image retargeting by texture-aware synthesis. IEEE Transactions on Visualization and Computer Graphics (TVCG), 2016, 22(2): 1088–1101 https://doi.org/10.1109/TVCG.2015.2440255
27	Dong W M, Bao G B, Zhang X P, Paul J C. Fast multi-operator image resizing and evaluation. Journal of Computer Science and Technology, 2012, 27(1): 121–134 https://doi.org/10.1007/s11390-012-1211-6
28	Wu H, Wang Y S, Feng K C, Wong T T, Lee T Y, Heng P A. Resizing by symmetry-summarization. ACM Transactions on Graphics, 2010, 29(6): 159 https://doi.org/10.1145/1882261.1866185
29	Itti L, Koch C, Niebur E. A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998 (11): 1254–1259 https://doi.org/10.1109/34.730558
30	Hu S M, Chen T, Xu K, Cheng M M, Martin R R. Internet visual media processing: a survey with graphics and vision applications. The Visual Computer, 2013, 29(5): 393–405 https://doi.org/10.1007/s00371-013-0792-6
31	Kraevoy V, Sheffer A, Shamir A, Cohen-Or D. Non-homogeneous resizing of complex models. ACM Transactions on Graphics, 2008, 27(5): 111 https://doi.org/10.1145/1409060.1409064
32	Wang K P, Zhang C M. Content-aware model resizing based on surface deformation. Computers & Graphics, 2009, 33(3): 433–438 https://doi.org/10.1016/j.cag.2009.03.004
33	Xiao C X, Jin L Q, Nie Y W, Wang R F, Sun H Q, Ma K L. Contentaware model resizing with symmetry-preservation. The Visual Computer, 2015, 31(2): 155–167 https://doi.org/10.1007/s00371-014-0919-4
34	Chen L, Meng X X. Anisotropic resizing of model with geometric textures. In: Proceedings of the 2009 SIAM/ACM Joint Conference on Geometric and Physical Modeling. 2009, 289–294 https://doi.org/10.1145/1629255.1629292
35	Lin J J, Cohen-Or D, Zhang H, Liang C, Sharf A, Deussen O, Chen B Q. Structure-preserving retargeting of irregular 3D architecture. ACM Transactions on Graphics, 2011, 30(6): 183 https://doi.org/10.1145/2070781.2024217
36	Shamir A, Sorkine O. Visual media retargeting. ACM SIGGRAPH ASIA 2009 Courses, 2009
37	Rubinstein M, Shamir A, Avidan S. Improved seam carving for video retargeting. ACM Transactions on Graphics, 2008, 27(3): 1–9 https://doi.org/10.1145/1360612.1360615
38	Chiang C K, Wang S F, Chen Y L, Lai S H. Fast JND-based video carving with GPU acceleration for real-time video retargeting. IEEE Transactions on Circuits and Systems for Video Technology, 2009, 19(11): 1588–1597 https://doi.org/10.1109/TCSVT.2009.2031462
39	Chao W L, Su H H, Chien S Y, Hsu W, Ding J J. Coarse-to-fine temporal optimization for video retargeting based on seam carving. In: Proceedings of the 2011 IEEE International Conference on Multimedia and Expo. 2011, 1–6 https://doi.org/10.1109/ICME.2011.6012025
40	Deselaers T, Dreuw P, Ney H. Pan, zoom, scan – time-coherent, trained automatic video cropping. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2008, 1–8 https://doi.org/10.1109/cvpr.2008.4587729
41	Fan X, Xie X, Zhou H Q, Ma W Y. Looking into video frames on small displays. In: Proceedings of the 11th ACM international conference on Multimedia. 2003, 247–250 https://doi.org/10.1145/957013.957063
42	Liu F, Gleicher M. Video retargeting: automating pan and scan. In: Proceedings of the 14th Annual ACM International Conference on Multimedia. 2006, 241–250 https://doi.org/10.1145/1180639.1180702
43	Kopf S, Haenselmann T, Farin D, Effelsberg W. Automatic generation of summaries for the Web. In: Yeung M M, Lienhart R W, Li C S, eds. Storage and Retrieval for Image and Video Databases, 2004, 417–428
44	Wolf L, Guttmann M, Cohen-Or D. Non-homogeneous content-driven video-retargeting. In: Proceedings of the 11th IEEE International Conference on Computer Vision. 2007, 1–6 https://doi.org/10.1109/iccv.2007.4409010
45	Zhang Y F, Hu S M, Martin R R. Shrinkability maps for content-aware video resizing. Computer Graphics Forum, 2008, 27(7): 1797–1804 https://doi.org/10.1111/j.1467-8659.2008.01325.x
46	Wang Y S, Fu H, Sorkine O, Lee T Y, Seidel H P. Motion-aware temporal coherence for video resizing. ACMTransactions on Graphics, 2009, 28(5): 127 https://doi.org/10.1145/1618452.1618473
47	Krähenbühl P, Lang M, Hornung A, Gross M. A system for retargeting of streaming video. ACM Transactions on Graphics, 2009, 28(5): 126 https://doi.org/10.1145/1618452.1618472
48	Kim J S, Kim J H, Kim C S. Adaptive image and video retargeting technique based on Fourier analysis. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. 2009, 1730–1737
49	Wang S F, Lai S H. Compressibility-aware media retargeting with structure preserving. IEEE Transactions on Image Processing, 2011, 20(3): 855–865 https://doi.org/10.1109/TIP.2010.2076293
50	Shi L, Wang J Q, Duan L Y, Lu H Q. Consumer video retargeting: context assisted spatial-temporal grid optimization. In: Proceedings of the 17th ACM International Conference on Multimedia. 2009, 301–310 https://doi.org/10.1145/1631272.1631315
51	Wang Y S, Lin H C, Sorkine O, Lee T Y. Motion-based video retargeting with optimized crop-and-warp. ACM Transactions on Graphics, 2010, 29(4): 90 https://doi.org/10.1145/1778765.1778827
52	Wang Y S, Hsiao J H, Sorkine O, Lee T Y. Scalable and coherent video resizing with per-frame optimization. ACM Transactions on Graphics, 2011, 30(4): 88 https://doi.org/10.1145/2010324.1964983
53	Yen T C, Tsai C M, Lin C W. Maintaining temporal coherence in video retargeting using mosaic-guided scaling. IEEE Transactions on Image Processing, 2011, 20(8): 2339–2351 https://doi.org/10.1109/TIP.2011.2114357
54	Khan S, Shah M. Object based segmentation of video using color, motion and spatial information. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2001 https://doi.org/10.1109/cvpr.2001.991039
55	Paris S. Edge-preserving smoothing and mean-shift segmentation of video streams. In: Forsyth D, Torr P, Zisserman A, eds. Computer Vision–ECCV 2008. Springer Berlin Heidelberg, 2008, 460–473 https://doi.org/10.1007/978-3-540-88688-4_34
56	Wang J, Thiesson B, Xu Y Q, Cohen M. Image and video segmentation by anisotropic kernel mean shift. In: Proceedings of the 10th European Conference on Computer Vision. 2004, 238–249 https://doi.org/10.1007/978-3-540-24671-8_19
57	Hu Y Q, Rajan D. Hybrid shift map for video retargeting. In: Proceedings of the 2010 IEEE Conference on Computer Vision and Pattern Recognition. 2010, 577–584 https://doi.org/10.1109/CVPR.2010.5540162
58	Yan B, Sun K R, Liu L. Matching area based seam carving for video retargeting. IEEE Transactions on Circuits and Systems for Video Technology. 2013, 23(2): 302–310 https://doi.org/10.1109/TCSVT.2012.2203740
59	Lin S S, Lin C H, Yeh I C, Chang S H, Yeh C K, Lee T Y. Contentaware video retargeting using object-preserving warping. IEEE Transactions on Visualization and Computer Graphics, 2013, 19(10): 1677–1686 https://doi.org/10.1109/TVCG.2013.75
60	Qu Z, Wang J Q, Xu M, Lu H Q. Context-aware video retargeting via graph model. IEEE Transactions on Multimedia, 2013, 15(7): 1677–1687 https://doi.org/10.1109/TMM.2013.2267727
61	Yuan Z, Lu T R, Huang Y, Wu D P, Yu H. Addressing visual consistency in video retargeting: a refined homogeneous approach. IEEE Transactions on Circuits and Systems for Video Technology, 2012, 22(6): 890–903 https://doi.org/10.1109/TCSVT.2011.2181230
62	Li B, Duan L Y, Wang J, Ji R, Lin C W, Gao W. Spatiotemporal grid flow for video retargeting. IEEE Transactions on Image Processing, 2014, 23(4): 1615–1628 https://doi.org/10.1109/TIP.2014.2305843
63	Nie Y W, Zhang Q, Wang R F, Xiao C X. Video retargeting combining warping and summarizing optimization. The Visual Computer, 2013, 29(6–8): 785–794 https://doi.org/10.1007/s00371-013-0830-4
64	Wang Z, Bovik A C, Sheikh H R, Simoncelli E P. Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing, 2004, 13(4): 600–612 https://doi.org/10.1109/TIP.2003.819861
65	Hsu C C, Lin C W, Fang Y, Lin W. Objective quality assessment for image retargeting based on perceptual geometric distortion and information loss. IEEE Journal of Selected Topics in Signal Processing, 2014, 8(3): 377–389 https://doi.org/10.1109/JSTSP.2014.2311884
66	Bare B, Li K, Wang W Y, Yan B. Learning to assess image retargeting. In: Proceedings of the 22nd ACM International Conference on Multimedia. 2014, 925–928 https://doi.org/10.1145/2647868.2654957
67	Rubinstein M, Gutierrez D, Sorkine O, Shamir A. A comparative study of image retargeting. ACM Transactions on Graphics, 2010, 29(6): 160 https://doi.org/10.1145/1882261.1866186
68	Pele O, Werman M. Fast and robust earth mover’s distances. In: Proceedings of the 12th IEEE international conference on Computer vision. 2009, 460–467 https://doi.org/10.1109/iccv.2009.5459199
69	Liu C, Yuen J, Torralba A, Sivic J, Freeman W T. Sift flow: dense correspondence across different scenes. In: Proceedings of the 10th European Conference on Computer Vision. 2008, 28–42 https://doi.org/10.1007/978-3-540-88690-7_3
70	Liu Y J, Luo X, Xuan Y M, Chen W F, Fu X L. Image retargeting quality assessment. Computer Graphics Forum, 2011, 30(2): 583–592 https://doi.org/10.1111/j.1467-8659.2011.01881.x
71	Zhang J, Kuo C C J. An objective quality of experience (QoE) assessment index for retargeted images. In: Proceedings of the ACM International Conference on Multimedia. 2014, 257–266 https://doi.org/10.1145/2647868.2654922
72	Fang Y M, Zeng K, Wang Z, Lin W S, Fang Z J, Lin C W. Objective quality assessment for image retargeting based on structural similarity. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2014, 4(1): 95–105 https://doi.org/10.1109/JETCAS.2014.2298919
73	Barnes C, Shechtman E, Finkelstein A, Goldman D. Patchmatch: a randomized correspondence algorithm for structural image editing. ACM Transactions on Graphics, 2009, 28(3): 24 https://doi.org/10.1145/1531326.1531330
74	Manjunath B S, Ohm J R, Vasudevan V V, Yamada A. Color and texture descriptors. IEEE Transactions on Circuits and Systems for Video Technology, 2001, 11(6): 703–715 https://doi.org/10.1109/76.927424
75	Simakov D, Caspi Y, Shechtman E, Irani M. Summarizing visual data using bidirectional similarity. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2008, 1–8 https://doi.org/10.1109/cvpr.2008.4587842
76	Kasutani E, Yamada A. The MPEG-7 color layout descriptor: a compact image feature description for high-speed image/video segment retrieval. In: Proceedings of the 2001 International Conference on Image Processing. 2001, 674–677 https://doi.org/10.1109/icip.2001.959135
77	Yan B, Yuan B H, Yang B. Effective video retargeting with jittery assessment. IEEE Transactions on Multimedia, 2014, 16(1): 272–277 https://doi.org/10.1109/TMM.2013.2286112
78	Tsai S S, Chen D, Takacs G, Chandrasekhar V, Singh J P, Girod B. Location coding for mobile image retrieval. In: Proceedings of the 5th International ICST Mobile Multimedia Communications Conference. 2009 https://doi.org/10.4108/ICST.MOBIMEDIA2009.7406
79	V Chandrasekhar V, Takacs G, Chen D, Tsai S, Grzeszczuk R, Girod B. Chog: compressed histogram of gradients a low bit-rate feature descriptor. In: Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition. 2009, 2504–2511
80	Lowe D G. Distinctive image features from scale-invariant keypoints. International journal of computer vision, 2004, 60(2): 91–110 https://doi.org/10.1023/B:VISI.0000029664.99615.94
81	Yang X Y, Liu L L, Qian X M, Mei T, Shen J L, Tian Q. Mobile visual search via hievarchical sparse coding. In: Proceedings of the 2014 IEEE International Conference on Multimedia and Expo. 2014, 1–6 https://doi.org/10.1109/icme.2014.6890294
82	Tan W M, Yan B, Li K, Tian Q. Image retargeting for preserving robust local feature: application to mobile visual search. IEEE Transactions on Multimedia, 2016, 18(1): 128–137 https://doi.org/10.1109/TMM.2015.2500727
83	Ke Y, Sukthankar R. PCA-SIFT: a more distinctive representation for local image descriptors. In: Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2004, 506–513
84	Seber G A F. Multivariate observations. John Wiley & Sons, 2009
85	Spath H. The cluster dissection and analysis theory FORTRAN programs examples. Prentice-Hall, Inc., 1985
86	Philbin J, Chum O, Isard M, Sivic J, Zisserman A. Object retrieval with large vocabularies and fast spatial matching. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2007, 1–8 https://doi.org/10.1109/cvpr.2007.383172
87	Nie L Q, Wang M, Gao Y, Zha Z J, Chua T S. Beyond text QA: multimedia answer generation by harvesting Web information. IEEE Transactions on Multimedia, 2013, 15(2): 426–441 https://doi.org/10.1109/TMM.2012.2229971
88	Nie L Q, Yan S C, Wang M, Hong R C, Chua T S. Harvesting visual concepts for image search with complex queries. In: Proceedings of the 20th ACM international conference on Multimedia. 2012, 59–68 https://doi.org/10.1145/2393347.2393363
89	Nie L Q, Wang M, Zha Z J, Chua T S. Oracle in image search: a content-based approach to performance prediction. ACM Transactions on Information Systems, 2012, 30(2): 13 https://doi.org/10.1145/2180868.2180875
90	Hong R C, Li G D, Nie L Q, Tang J H, Chua T S. Exploring large scale data for multimedia QA: an initial study. In: proceedings of the ACM International Conference on Image and Video Retrieval. 2010, 74–81 https://doi.org/10.1145/1816041.1816055
91	Lu S P, Dauphin G, Lafruit G, Munteanu A. Color retargeting: interactive time-varying color image composition from time-lapse sequences. Computational Visual Media, 2015, 1(4): 321–330 https://doi.org/10.1007/s41095-015-0031-3
92	Guo Y W, Liu M, Gu T T, Wang W P. Improving photo composition elegantly: considering image similarity during composition optimization. Computer Graphics Forum, 2012, 31(7): 2193–2202 https://doi.org/10.1111/j.1467-8659.2012.03212.x
93	Zhang F L, Wang M, Hu S M. Aesthetic image enhancement by dependence-aware object recomposition. IEEE Transactions on Multimedia, 2013, 15(7): 1480–1490 https://doi.org/10.1109/TMM.2013.2268051
94	Li K, Yan B, Li J, Majumder A. Seam carving based aesthetics enhancement for photos. Signal Processing: Image Communication, 2015, 39: 509–516 https://doi.org/10.1016/j.image.2015.07.005
95	Bertalmio M, Sapiro G, Caselles V, Ballester C. Image in-painting. In: Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques. 2000, 417–424
96	Yeung M M, Yeo B L. Video visualization for compact presentation and fast browsing of pictorial content. IEEE Transactions on Circuits and Systems for Video Technology, 1997, 7(5): 771–785 https://doi.org/10.1109/76.633496
97	Oh J, Wen Q, Lee J, Hwang S, Video abstraction. Hershey, PA: Idea Group Inc. and IRM Press, 2004
98	Liu T M, Zhang H J, Qi F H. A novel video key-frame-extraction algorithm based on perceived motion energy model. IEEE Transactions on Circuits and Systems for Video Technology, 2003, 13(10): 1006–1013 https://doi.org/10.1109/TCSVT.2003.816521
99	Hanjalic A, Zhang H J. An integrated scheme for automated video abstraction based on unsupervised cluster-validity analysis. IEEE Transactions on Circuits and Systems for Video Technology, 1999, 9(8): 1280–1289 https://doi.org/10.1109/76.809162
100	You J Y, Liu G Z, Sun L, Li H L. A multiple visual models based perceptive analysis framework for multilevel video summarization. IEEE Transactions on Circuits and Systems for Video Technology, 2007, 17(3): 273–285 https://doi.org/10.1109/TCSVT.2007.890857
101	Qu W, Zhang Y F, Wang D L, Feng S, Yu G. Semantic movie summarization based on string of IE-RoleNets. Computational Visual Media, 2015, 1(2): 129–141 https://doi.org/10.1007/s41095-015-0015-3
102	Pritch Y, Rav-Acha A, Peleg S. Nonchronological video synopsis and indexing. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008, 30(11): 1971–1984 https://doi.org/10.1109/TPAMI.2008.29
103	Lu S P, Zhang S H, Wei J, Hu S M, Martin R R. Timeline editing of objects in video. IEEE Transactions on Visualization and Computer Graphics, 2013, 19(7): 1218–1227 https://doi.org/10.1109/TVCG.2012.145
104	Nie Y W, Sun H Q, Li P, Xiao C X, Ma K L. Object movements synopsis via part assembling and stitching. IEEE Transactions on Visualization and Computer Graphics, 2014, 20(9): 1303–1315 https://doi.org/10.1109/TVCG.2013.2297931
105	Nie Y W, Xiao C X, Sun H Q, Li P. Compact video synopsis via global spatiotemporal optimization. IEEE Transactions on Visualization and Computer Graphics, 2013, 19(10): 1664–1676 https://doi.org/10.1109/TVCG.2012.176
106	Li K, Yan B, Wang W, Gharavi H. An effective video synopsis approach with seam carving. IEEE Signal Processing Letters, 2016, 23(1): 11–14 https://doi.org/10.1109/LSP.2015.2496558
107	Lee D S. Effective Gaussian mixture learning for video background subtraction. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(5): 827–832 https://doi.org/10.1109/TPAMI.2005.102
108	Li Z, Ishwar P, Konrad J. Video condensation by ribbon carving. IEEE Transactions on Image Processing, 2009, 18(11): 2572–2583 https://doi.org/10.1109/TIP.2009.2026677

[1]

Supplementary Material

Download

[1]	Ying LI, Xiangwei KONG, Haiyan FU, Qi TIAN. Contextual modeling on auxiliary points for robust image reranking[J]. Front. Comput. Sci., 2019, 13(5): 1010-1022.
[2]	Kun SU, Gongping YANG, Lu YANG, Peng SU, Yilong YIN. Non-negative locality-constrained vocabulary tree for finger vein image retrieval[J]. Front. Comput. Sci., 2019, 13(2): 318-332.
[3]	Xiang FENG, Wanggen WAN, Richard Yi Da XU, Haoyu CHEN, Pengfei LI, J. Alfredo SÁNCHEZ. A perceptual quality metric for 3D triangle meshes based on spatial pooling[J]. Front. Comput. Sci., 2018, 12(4): 798-812.
[4]	Xueming WANG, Zechao LI, Jinhui TANG. Visual understanding by mining social media: recent advances and challenges[J]. Front. Comput. Sci., 2018, 12(3): 406-422.
[5]	Le DONG, Wenpu DONG, Ning FENG, Mengdie MAO, Long CHEN, Gaipeng KONG. Color space quantization-based clustering for image retrieval[J]. Front. Comput. Sci., 2017, 11(6): 1023-1035.
[6]	Ge SONG,Xiaoyang TAN. Hierarchical deep hashing for image retrieval[J]. Front. Comput. Sci., 2017, 11(2): 253-265.
[7]	Li CUI. SWVFS: a saliency weighted visual feature similarity metric for image quality assessment[J]. Front. Comput. Sci., 2014, 8(1): 145-155.
[8]	Zhiyi MA, Xiao HE, Chao LIU. Assessing the quality of metamodels[J]. Front Comput Sci, 2013, 7(4): 558-570.

Viewed

Full text

Abstract

Cited

Shared

Discussed