caa a22 4500 445322438 CHVBK 20180317142708.0 cr unu---uuuuu 170323e20111001xx s 000 0 eng 10.1007/s00530-010-0225-6 doi (NATIONALLICENCE)springer-10.1007/s00530-010-0225-6 Semi-automatic cartoon generation by motion planning [Elektronische Daten] [Jun Yu, Dacheng Tao, Meng Wang, Jun Cheng] To reduce tedious work in cartoon animation, some computer-assisted systems including automatic Inbetweening and cartoon reusing systems have been proposed. In existing automatic Inbetweening systems, accurate correspondence construction, which is a prerequisite for Inbetweening, cannot be achieved. For cartoon reusing systems, the lack of efficient similarity estimation method and reusing mechanism makes it impractical for the users. The semi-supervised graph-based cartoon reusing approach proposed in this paper aims at generating smooth cartoons from the existing data. In this approach, the similarity between cartoon frames can be accurately evaluated by calculating the distance based on local shape context, which is expected to be rotation and scaling invariant. By the semi-supervised algorithm, given an initial frame, the most similar cartoon frames in the cartoon library are selected as candidates of the next frame. The smooth cartoons can be generated by carrying out the algorithm repeatedly to select new cartoon frames after the cartoonists specifying the motion path in a background image. Experimental results of the candidate frame selection in our cartoon dataset suggest the effectiveness of the proposed local shape context for similarity evaluation. The other experiments show the excellent performance on cartoon generation of our approach. Springer-Verlag, 2010 Cartoon reusing nationallicence Semi-supervised nationallicence Local shape context nationallicence Similarity nationallicence Motion path nationallicence Yu Jun School of Computer Engineering, Nanyang Technological University, BLK N4-2b, Nanyang Avenue, 636798, Singapore, Singapore aut Tao Dacheng Faculty of Engineering and Information Technology, Centre for Quantum Computation and Intelligent Systems, University of Technology, Broadway, 2007, Sydney, NSW, Australia aut Wang Meng School of Computing, National University of Singapore, Singapore, Singapore aut Cheng Jun Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China aut Multimedia Systems Springer-Verlag 17/5(2011-10-01), 409-419 0942-4962 17:5<409 2011 17 530 https://doi.org/10.1007/s00530-010-0225-6 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00530-010-0225-6 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Yu Jun School of Computer Engineering, Nanyang Technological University, BLK N4-2b, Nanyang Avenue, 636798, Singapore, Singapore aut NATIONALLICENCE 700 1- Tao Dacheng Faculty of Engineering and Information Technology, Centre for Quantum Computation and Intelligent Systems, University of Technology, Broadway, 2007, Sydney, NSW, Australia aut NATIONALLICENCE 700 1- Wang Meng School of Computing, National University of Singapore, Singapore, Singapore aut NATIONALLICENCE 700 1- Cheng Jun Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China aut NATIONALLICENCE 773 0- Multimedia Systems Springer-Verlag 17/5(2011-10-01), 409-419 0942-4962 17:5<409 2011 17 530 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer