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Proceedings ArticleDOI

Stereoscopic image retargeting based on 3D saliency detection

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TLDR
Experimental results demonstrated that both the proposed visual attention model and the proposed retargeting method outperform the state-of-the-art studies.
Abstract
In this paper, we propose a novel stereoscopic image retargeting algorithm based on 3D visual saliency detection. A new 3D visual attention model is designed based on 2D visual feature detection, depth feature detection and the modeling of various viewing bias in stereo vision. A geometrically consistent seam carving technique is adopted for retargeting stereo image pair. Experimental results demonstrated that both the proposed visual attention model and the proposed retargeting method outperform the state-of-the-art studies.

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Citations
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Journal ArticleDOI

Salient object detection for RGB-D image by single stream recurrent convolution neural network

TL;DR: Extensive quantitative and qualitative experimental evaluations on four dataset demonstrate that the proposed SSRCNN method outperforms most state-of-the-art methods.
Journal ArticleDOI

Depth-Preserving Stereo Image Retargeting Based on Pixel Fusion

TL;DR: A pixel fusion-based stereo image retargeting method, which could adaptively retarget stereo images with flexible aspect ratios, simultaneously preserving the depth and shape preservation, is proposed.
Journal ArticleDOI

QoE-Guided Warping for Stereoscopic Image Retargeting

TL;DR: Experimental results demonstrate that in comparison with the existing stereoscopic image retargeting methods, the proposed method can achieve a reasonable performance optimization among the QoE’s factors of image quality, visual comfort, and depth perception, leading to promising overall S3D experience.
Journal ArticleDOI

Saliency-based stereoscopic image retargeting

TL;DR: Experimental results have shown that both the stereoscopic saliency detection and image retargeting methods can obtain better performance than the existing related methods on the public databases.
Journal ArticleDOI

A dataset of stereoscopic images and ground-truth disparity mimicking human fixations in peripersonal space

TL;DR: A rendering methodology is implemented in which the camera pose mimics realistic eye pose for a fixating observer, thus including convergent eye geometry and cyclotorsion and creating a stereoscopic dataset useful for a number of problems relevant to human and computer vision.
References
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Proceedings ArticleDOI

Learning Conditional Random Fields for Stereo

TL;DR: This paper has constructed a large number of stereo datasets with ground-truth disparities, and a subset of these datasets are used to learn the parameters of conditional random fields (CRFs) and presents experimental results illustrating the potential of this approach for automatically learning the Parameters of models with richer structure than standard hand-tuned MRF models.
Journal ArticleDOI

Nonlinear disparity mapping for stereoscopic 3D

TL;DR: The most important perceptual aspects of stereo vision are discussed and their implications for stereoscopic content creation are formalized into a set of basic disparity mapping operators that enable us to control and retarget the depth of a stereoscopic scene in a nonlinear and locally adaptive fashion.
Journal ArticleDOI

Quantifying center bias of observers in free viewing of dynamic natural scenes.

TL;DR: These results demonstrate quantitatively for the first time that center bias is correlated strongly with photographer bias and is influenced by viewing strategy at scene onset, while orbital reserve, screen center, and motor bias contribute minimally.
Journal ArticleDOI

Saliency Detection in the Compressed Domain for Adaptive Image Retargeting

TL;DR: The proposed image retargeting algorithm effectively preserves the visually important regions for images, efficiently removes the less crucial regions, and therefore significantly outperforms the relevant state-of-the-art algorithms, as demonstrated with the in-depth analysis in the extensive experiments.
Proceedings ArticleDOI

A survey of image retargeting techniques

TL;DR: This work review and categorize algorithms for contentaware image retargeting, i.e., resizing an image while taking its content into consideration to preserve important regions and minimize distortions, as it requires preserving the relevant information while maintaining an aesthetically pleasing image for the user.
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