Depth Discontinuities by Pixel-to-Pixel Stereo
International Journal of Computer Vision
A Computational Model of Depth-Based Attention
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume IV-Volume 7472 - Volume 7472
Detecting Salient Motion by Accumulating Directionally-Consistent Flow
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Visual Correspondence Using Energy Minimization and Mutual Information
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Contrast-based image attention analysis by using fuzzy growing
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
An Integrated Model of Top-Down and Bottom-Up Attention for Optimizing Detection Speed
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Automatic scaling and cropping of videos for devices with limited screen resolution
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Stereo Processing by Semiglobal Matching and Mutual Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust digital watermarking in videos based on geometric transformations
Proceedings of the international conference on Multimedia
Algorithms for video retargeting
Multimedia Tools and Applications
3D saliency for abnormal motion selection: the role of the depth map
ICVS'11 Proceedings of the 8th international conference on Computer vision systems
A biologically inspired computational model for image saliency detection
MM '11 Proceedings of the 19th ACM international conference on Multimedia
SeamCrop: changing the size and aspect ratio of videos
Proceedings of the 4th Workshop on Mobile Video
Stereoscopic visual attention model for 3d video
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
Global contrast based salient region detection
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
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We present a novel system for automatically detecting salient image regions in stereoscopic videos. Our proposed algorithm considers information based on three dimensions: salient colors in individual frames, salient information derived from camera and object motion, and depth saliency. These three components are dynamically combined into one final saliency map based on the reliability of the individual saliency detectors. Such a combination allows using more efficient algorithms even if the quality of one detector degrades. For example, we use a computationally efficient stereo correspondence algorithm that might cause noisy disparity maps for certain scenarios. In this case, however, a more reliable saliency detection algorithm such as the image saliency is preferred. To evaluate the quality of the saliency detection, we created modified versions of stereoscopic videos with the non-salient regions blurred. Having users rate the quality of these videos, the results show that most users do not detect the blurred regions and that the automatic saliency detection is very reliable.