Paper ID | TEC-5.2 | ||
Paper Title | FAST HYBRID IMAGE RETARGETING | ||
Authors | Daniel Valdez-Balderas, Oleg Muraveynyk, Timothy Smith, Samsung, United Kingdom | ||
Session | TEC-5: Image and Video Processing 1 | ||
Location | Area G | ||
Session Time: | Monday, 20 September, 13:30 - 15:00 | ||
Presentation Time: | Monday, 20 September, 13:30 - 15:00 | ||
Presentation | Poster | ||
Topic | Image and Video Processing: Formation and reconstruction | ||
IEEE Xplore Open Preview | Click here to view in IEEE Xplore | ||
Abstract | Image retargeting changes the aspect ratio of images while aiming to preserve content and minimise noticeable distortion. Fast and high-quality methods are particularly relevant at present, due to the large variety of image and display aspect ratios. We propose a retargeting method that quantifies and limits warping distortions with the use of contentaware cropping. The pipeline of the proposed approach consists of the following steps. First, an importance map of a source image is generated using deep semantic segmentation and saliency detection models. Then, a preliminary warping mesh is computed using axis aligned deformations, enhanced with the use of a distortion measure to ensure low warping deformations. Finally, the retargeted image is produced using a content-aware cropping algorithm. In order to evaluate our method, we perform a user study based on the RetargetMe benchmark. Experimental analyses show that our method outperforms recent approaches, while running in a fraction of their execution time. |