TY - JOUR
T1 - Depth-based stereoscopic projection approach for 3D saliency detection
AU - Lin, Hongyun
AU - Lin, Chunyu
AU - Zhao, Yao
AU - Xiao, Jimin
AU - Tillo, Tammam
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - With the popularity of 3D display and the widespread using of depth camera, 3D saliency detection is feasible and significant. Different with 2D saliency detection, 3D saliency detection increases an additional depth channel so that we need to take the influence of depth and binocular parallax into account. In this paper, a new depth-based stereoscopic projection approach is proposed for 3D visual salient region detection. 3D images reconstructed with color and depth images are respectively projected onto XOZ plane and YOZ plane with the specific direction. We find some obvious characteristics that help us to remove the background and progressive surface where the depth is from the near to the distant so that the salient regions are detected more accurately. Then depth saliency map (DSM) is created, which is combined with 2D saliency map to obtain a final 3D saliency map. Our approach performs well in removing progressive surface and background which are difficult to be detected in 2D saliency detection.
AB - With the popularity of 3D display and the widespread using of depth camera, 3D saliency detection is feasible and significant. Different with 2D saliency detection, 3D saliency detection increases an additional depth channel so that we need to take the influence of depth and binocular parallax into account. In this paper, a new depth-based stereoscopic projection approach is proposed for 3D visual salient region detection. 3D images reconstructed with color and depth images are respectively projected onto XOZ plane and YOZ plane with the specific direction. We find some obvious characteristics that help us to remove the background and progressive surface where the depth is from the near to the distant so that the salient regions are detected more accurately. Then depth saliency map (DSM) is created, which is combined with 2D saliency map to obtain a final 3D saliency map. Our approach performs well in removing progressive surface and background which are difficult to be detected in 2D saliency detection.
KW - 3D saliency detection
KW - Depth-based stereoscopic projection
KW - Salient region
UR - http://www.scopus.com/inward/record.url?scp=84984650289&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-24075-6_64
DO - 10.1007/978-3-319-24075-6_64
M3 - Conference article
AN - SCOPUS:84984650289
SN - 0302-9743
VL - 9314
SP - 664
EP - 673
JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 16th Pacific-Rim Conference on Multimedia, PCM 2015
Y2 - 16 September 2015 through 18 September 2015
ER -