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• W2765509710 abstract "Retinal prosthesis devices have shown great value in restoring some sight for individuals with profoundly impaired vision, but the visual acuity and visual field provided by prostheses greatly limit recipients' visual experience. In this paper, we employ computer vision approaches to seek to expand the perceptible visual field in patients implanted potentially with a high-density retinal prosthesis while maintaining visual acuity as much as possible.We propose an optimized content-aware image retargeting method, by introducing salient object detection based on color and intensity-difference contrast, aiming to remap important information of a scene into a small visual field and preserve their original scale as much as possible. It may improve prosthetic recipients' perceived visual field and aid in performing some visual tasks (e.g. object detection and object recognition). To verify our method, psychophysical experiments, detecting object number and recognizing objects, are conducted under simulated prosthetic vision. As control, we use three other image retargeting techniques, including Cropping, Scaling, and seam-assisted shrinkability.Results show that our method outperforms in preserving more key features and has significantly higher recognition accuracy in comparison with other three image retargeting methods under the condition of small visual field and low-resolution.The proposed method is beneficial to expand the perceived visual field of prosthesis recipients and improve their object detection and recognition performance. It suggests that our method may provide an effective option for image processing module in future high-density retinal implants." @default.
• W2765509710 created "2017-11-10" @default.
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• W2765509710 date "2018-02-16" @default.
• W2765509710 modified "2023-10-16" @default.
• W2765509710 title "An optimized content-aware image retargeting method: toward expanding the perceived visual field of the high-density retinal prosthesis recipients" @default.
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• W2765509710 doi "https://doi.org/10.1088/1741-2552/aa966d" @default.
• W2765509710 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/29076459" @default.
• W2765509710 hasPublicationYear "2018" @default.
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