How does the shape descriptor measure the perceptual quality of the retargeting image?

Perceptual quality evaluation of the retargeting image plays an important role in benchmarking different retargeting methods, as well as guiding or optimizing the retargeting process. The distortions introduced during the retargeting process are mainly categorized into shape distortion and content information loss [1]. The shape distortion measurement is critical to the evaluation of retargeting image perceptual quality. In this paper, the performances of different shape descriptors, such as PHOW [2], GIST [3], MPEG-7 descriptors [4], EMD [5], for evaluating the perceptual quality of the retargeting image are examined based on the public image retargeting subjective quality database [6]. Experimental results demonstrated that most of the shape descriptors can hardly capture the characteristics representing the quality of the retargeting image, but the global shape descriptor GIST [3] presents significant performance gains. Moreover, by incorporating with the measurements from the perspective of content information loss, a better performance is further obtained.

[1]  Weisi Lin,et al.  Perceptual visual quality metrics: A survey , 2011, J. Vis. Commun. Image Represent..

[2]  O. Sorkine,et al.  Optimized scale-and-stretch for image resizing , 2008, SIGGRAPH 2008.

[3]  Yael Pritch,et al.  Shift-map image editing , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[4]  Michael Werman,et al.  Fast and robust Earth Mover's Distances , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[5]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[6]  Andrew Zisserman,et al.  Image Classification using Random Forests and Ferns , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[7]  Andrea Vedaldi,et al.  Vlfeat: an open and portable library of computer vision algorithms , 2010, ACM Multimedia.

[8]  Denis Simakov,et al.  Summarizing visual data using bidirectional similarity , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[9]  Ariel Shamir,et al.  Seam Carving for Content-Aware Image Resizing , 2007, ACM Trans. Graph..

[10]  Weiming Dong,et al.  Optimized image resizing using seam carving and scaling , 2009, SIGGRAPH 2009.

[11]  Zhou Wang,et al.  Modern Image Quality Assessment , 2006, Modern Image Quality Assessment.

[12]  Alan C. Bovik,et al.  Mean squared error: Love it or leave it? A new look at Signal Fidelity Measures , 2009, IEEE Signal Processing Magazine.

[13]  Ariel Shamir,et al.  A comparative study of image retargeting , 2010, SIGGRAPH 2010.

[14]  Eli Shechtman,et al.  PatchMatch: a randomized correspondence algorithm for structural image editing , 2009, ACM Trans. Graph..

[15]  Olga Sorkine-Hornung,et al.  A comparative study of image retargeting , 2010, ACM Trans. Graph..

[16]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[17]  S. Avidan,et al.  Multi-operator media retargeting , 2009, SIGGRAPH 2009.

[18]  Yong-Jin Liu,et al.  Image Retargeting Quality Assessment , 2011, Comput. Graph. Forum.

[19]  B. S. Manjunath,et al.  Color and texture descriptors , 2001, IEEE Trans. Circuits Syst. Video Technol..

[20]  King Ngi Ngan,et al.  Image Retargeting Quality Assessment: A Study of Subjective Scores and Objective Metrics , 2012, IEEE Journal of Selected Topics in Signal Processing.

[21]  Kai Zeng,et al.  Objective Quality Assessment for Image Retargeting Based on Structural Similarity , 2014, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.

[22]  Antonio Torralba,et al.  SIFT Flow: Dense Correspondence across Different Scenes , 2008, ECCV.

[23]  Antonio Torralba,et al.  Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope , 2001, International Journal of Computer Vision.

[24]  Ariel Shamir,et al.  Cropping Scaling Seam carving Warping Multi-operator , 2009 .

[25]  Sugato Chakravarty,et al.  Methodology for the subjective assessment of the quality of television pictures , 1995 .