TY - JOUR
T1 - An object-based approach to image/video-based synthesis and processing for 3-D and multiview televisions
AU - Chan, Shing Chow
AU - Gan, Zhi Feng
AU - Ng, King To
AU - Ho, Ka Leung
AU - Shum, Heung Yeung
PY - 2009/6
Y1 - 2009/6
N2 - This paper proposes an object-based approach to a class of dynamic image-based representations called "plenoptic videos," where the plenoptic video sequences are segmented into image-based rendering (IBR) objects each with its image sequence, depth map, and other relevant information such as shape and alpha information. This allows desirable functionalities such as scalability of contents, error resilience, and interactivity with individual IBR objects to be supported. Moreover, the rendering quality in scenes with large depth variations can also be improved considerably. A portable capturing system consisting of two linear camera arrays was developed to verify the proposed approach. An important step in the object-based approach is to segment the objects in video streams into layers or IBR objects. To reduce the time for segmenting plenoptic videos under the semiautomatic technique, a new object tracking method based on the level-set method is proposed. Due to possible segmentation errors around object boundaries, natural matting with Bayesian approach is also incorporated into our system. Furthermore, extensions of conventional image processing algorithms to these IBR objects are studied and illustrated with examples. Experimental results are given to illustrate the efficiency of the tracking, matting, rendering, and processing algorithms under the proposed object-based framework.
AB - This paper proposes an object-based approach to a class of dynamic image-based representations called "plenoptic videos," where the plenoptic video sequences are segmented into image-based rendering (IBR) objects each with its image sequence, depth map, and other relevant information such as shape and alpha information. This allows desirable functionalities such as scalability of contents, error resilience, and interactivity with individual IBR objects to be supported. Moreover, the rendering quality in scenes with large depth variations can also be improved considerably. A portable capturing system consisting of two linear camera arrays was developed to verify the proposed approach. An important step in the object-based approach is to segment the objects in video streams into layers or IBR objects. To reduce the time for segmenting plenoptic videos under the semiautomatic technique, a new object tracking method based on the level-set method is proposed. Due to possible segmentation errors around object boundaries, natural matting with Bayesian approach is also incorporated into our system. Furthermore, extensions of conventional image processing algorithms to these IBR objects are studied and illustrated with examples. Experimental results are given to illustrate the efficiency of the tracking, matting, rendering, and processing algorithms under the proposed object-based framework.
KW - Dynamic image-based representations
KW - Image-based rendering (iBR)
KW - Object-based
KW - Plenoptic videos
UR - https://www.webofscience.com/wos/woscc/full-record/WOS:000267608100004
UR - https://www.scopus.com/pages/publications/67649559306
U2 - 10.1109/TCSVT.2009.2017302
DO - 10.1109/TCSVT.2009.2017302
M3 - Journal Article
SN - 1051-8215
VL - 19
SP - 821
EP - 831
JO - IEEE Transactions on Circuits and Systems for Video Technology
JF - IEEE Transactions on Circuits and Systems for Video Technology
IS - 6
M1 - 4801605
ER -