How Real is Really? A Perceptually Motivated System for Quantifying Visual Realism in Digital Images

Contemporary video games are generally designed with the aim of engendering a state of immersion in their players. A sense of 'presence' is considered to be a prerequisite of total immersion, the ultimate level of immersion, and can be directly related to the degree of realism in the simulation presented in a videogame. However, continuously increasing the degree of visual realism in an image could cause adverse effects such as fault amplification and more importantly, emotions like fear and dread of the uncanny. It can also substantially raise the development costs of a game. Consequently, videogame developers would benefit greatly from knowing the threshold beyond which increased realism is counter-productive. This paper details the development of an image processing system that measures the degree of realism of an image using three methods - gradient variance, color variance and shadow softness - derived from existing theories and practices in perceptual psychology, photoforensics and image processing. It then discusses testing of the system on a variety of photographic and video game images.

[1]  J. Graftieaux [The uncanny]. , 2011, Annales francaises d'anesthesie et de reanimation.

[2]  Feng Pan,et al.  Discriminating between photorealistic computer graphics and natural images using fractal geometry , 2009, Science in China Series F: Information Sciences.

[3]  Rajesh Vasa,et al.  Growth and Change Dynamics in Open Source Software Systems , 2010 .

[4]  Siwei Lyu,et al.  How realistic is photorealistic , 2005 .

[5]  Oscar Nierstrasz,et al.  Comparative analysis of evolving software systems using the Gini coefficient , 2009, 2009 IEEE International Conference on Software Maintenance.

[6]  Juan Su,et al.  An automatic shadowdetection and compensation method for remote sensed color images , 2006, 2006 8th international Conference on Signal Processing.

[7]  Alan Chalmers,et al.  Psychophysically based artistic techniques for increased perceived realism of virtual environments , 2003, AFRIGRAPH '03.

[8]  Heinrich H. Bülthoff,et al.  Evaluating the perceptual realism of animated facial expressions , 2008, TAP.

[9]  Edward Cutrell,et al.  Measuring the Perception of Visual Realism in Images , 2001, Rendering Techniques.

[10]  Frans Mäyrä,et al.  An introduction to game studies , 2008 .

[11]  Victor J. D. Tsai,et al.  A comparative study on shadow compensation of color aerial images in invariant color models , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[12]  Shih-Fu Chang,et al.  Physics-motivated features for distinguishing photographic images and computer graphics , 2005, ACM Multimedia.

[13]  Shih-Fu Chang,et al.  Classifying Photographic and Photorealistic Computer Graphic Images using Natural Image Statistics , 2006 .

[14]  N. Otsu A threshold selection method from gray level histograms , 1979 .

[15]  Mel Slater,et al.  The Influence of Dynamic Shadows on Presence in Immersive Virtual Environments , 1995, Virtual Environments.

[16]  Nasir D. Memon,et al.  Blind source camera identification , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[17]  Qiming Qin,et al.  Shadow Segmentation and Compensation in High Resolution Satellite Images , 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium.

[18]  Riad I. Hammoud,et al.  Estimating the photorealism of images: distinguishing paintings from photographs , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[19]  Jakob J. Verbeek,et al.  Ranking User-annotated Images for Multiple Query Terms , 2009, BMVC.

[20]  F. Gobet Using a Cognitive Architecture for Addressing the Question of Cognitive Universals in Cross-Cultural Psychology , 2009 .

[21]  P J Kellman,et al.  Object and observer motion in the perception of objects by infants. , 1987, Journal of experimental psychology. Human perception and performance.

[22]  Jonathan Steuer,et al.  Defining virtual reality: dimensions determining telepresence , 1992 .

[23]  C. Frankel,et al.  Distinguishing photographs and graphics on the World Wide Web , 1997, 1997 Proceedings IEEE Workshop on Content-Based Access of Image and Video Libraries.

[24]  Heloir,et al.  The Uncanny Valley , 2019, The Animation Studies Reader.

[25]  Ann McNamara,et al.  Visual Perception in Realistic Image Synthesis , 2001, Comput. Graph. Forum.

[26]  Hany Farid,et al.  Exposing digital forgeries by detecting inconsistencies in lighting , 2005, MM&Sec '05.

[27]  Paul A. Cairns,et al.  A grounded investigation of game immersion , 2004, CHI EA '04.

[28]  Jospeh Nechvatal Immersive ideals/critical distances: a study of the affinity between artistic ideologies based in virtual reality and previous immersive idioms , 1999 .

[29]  Shih-Fu Chang,et al.  An online system for classifying computer graphics images from natural photographs , 2006, Electronic Imaging.

[30]  Mel Slater,et al.  Visual Realism Enhances Realistic Response in an Immersive Virtual Environment , 2009, IEEE Computer Graphics and Applications.

[31]  Nenghai Yu,et al.  Passive detection of doctored JPEG image via block artifact grid extraction , 2009, Signal Process..

[32]  D. Hubel,et al.  Receptive fields, binocular interaction and functional architecture in the cat's visual cortex , 1962, The Journal of physiology.