Results 141 to 150 of about 1,672 (192)

Automatic image retargeting [PDF]

open access: yesACM SIGGRAPH 2004 Sketches on - SIGGRAPH '04, 2004
We present a non-photorealistic algorithm for retargeting large images to small size displays, particularly on mobile devices. This method adapts large images so that important objects in the image are still recognizable when displayed at a lower target resolution. Existing image manipulation techniques such as cropping works well for images containing
Vidya Setlur   +4 more
openaire   +2 more sources

Scene Text Aware Image Retargeting [PDF]

open access: yes2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2019
Extensive use of text labels and symbols available in the digital media for interpretation and communication of information has gained a lot of attention in the era of digital media. Access of the images with scene text in it through different display devices tend to deform the scene text region while resizing for better viewing experience.
Diptiben Patel, Shanmuganathan Raman
openaire   +2 more sources

Perceptual Relevance Based Image Retargeting [PDF]

open access: yesIEEE Signal Processing Letters, 2015
The impact of perceptual relevance information on content aware image retargeting is investigated. We integrated fixation density maps and region-of-interest maps into a contemporary image retargeting algorithm to test the hypothesis that the latter result in superior performance given their object level representation.
Ulrich Engelke   +2 more
openaire   +2 more sources

Image Retargeting Using Mesh Parametrization

IEEE Transactions on Multimedia, 2009
Image retargeting aims to adapt images to displays of small sizes and different aspect ratios. Effective retargeting requires emphasizing the important content while retaining surrounding context with minimal visual distortion. In this paper, we present such an effective image retargeting method using saliency-based mesh parametrization.
Michael Gleicher, Yanwen Guo
exaly   +2 more sources

Saliency-based stereoscopic image retargeting

Information Sciences, 2016
Abstract In this paper, we propose a new saliency based stereoscopic image retargeting method based on the characteristics of the Human Visual System (HVS). A new stereoscopic saliency detection method is designed by adopting low-level features of intensity, color, texture and depth.
Weisi Lin   +2 more
exaly   +3 more sources

Fast structure-preserving image retargeting [PDF]

open access: yes2009 IEEE International Conference on Acoustics, Speech and Signal Processing, 2009
Several different methods have been proposed for image/video retargeting while retaining the content. However, they sometimes produce some artifacts, such as ridge or structure twist. In this paper, we present a structure-preserving image resizing technique for the image retargeting applications.
Shu-Fan Wang, Shang-Hong Lai
openaire   +2 more sources

Springs-based simulation for image retargeting [PDF]

open access: yes2011 18th IEEE International Conference on Image Processing, 2011
In this paper an efficient method for image retargeting is proposed. It relies onto a mechanical model based on springs network. Each pixel displacement (compression or expansion) is given by the network response, according to the springs stiffness. The properties of the springs are determined as function of the visual relevance of the pixels.
GALLEA, Roberto   +2 more
openaire   +3 more sources

A comparative study of image retargeting [PDF]

open access: yesACM Transactions on Graphics, 2010
The numerous works on media retargeting call for a methodological approach for evaluating retargeting results. We present the first comprehensive perceptual study and analysis of image retargeting.
Diego Gutierrez   +2 more
exaly   +2 more sources

A comprehensive review of image retargeting

Neurocomputing
Zhong Zhang   +2 more
exaly   +2 more sources

Deep Supervised Image Retargeting

2021 IEEE International Conference on Multimedia and Expo (ICME), 2021
Recent learning-based image retargeting methods have achieved significant improvement. However, two main is-sues remain in this challenging task: (i) it is difficult to build ground truth datasets for supervised learning; (ii) most methods are based on a certain operator, not suitable for various images with different target sizes.
Yijing Mei   +4 more
openaire   +1 more source

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