Volume 9 Issue 9 - July 24, 2009 PDF
Self-Animating Images: Illusory Motion Using Repeated Asymmetric Patterns
Ming-Te Chi1, Tong-Yee Lee1,*, Yingge Qu2 and Tien-Tsin Wong2

1Department of Computer Science and Information Engineering, College of Electrical Engineering and Computer Science, National Cheng Kung University
2Department of Computer Science and Engineering, The Chinese University of Hong Kong

ACM Transactions on Graphics (SIGGRAPH 2008 issue), Vol. 27, No. 3, August 2008, pp. 62:1-62:8.

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Project Web Site: http://graphics.csie.ncku.edu.tw/SAI/

(1) our work is selected as one of four highlight papers from 518 ACM SIGGRAPH 2008 technical paper submissions and 2) a recent article (2008 Sept. Issue) published at Newsweek/Russia reports our research. 

Our visual system is much more complicated than a state-of-the-art camera. “I know it when I see it” may not always be correct, because sometimes our visual system misleads us. Illusory motion is a very interesting phenomenon characterized by apparent motion in a still image. For example, Kitaoka [1] demonstrated a remarkable illusion art called “Rotating snakes”. This example (Figure 1) shows a very strong illusory motion that can be perceived in a single image. The circular snakes appear to rotate “spontaneously,” although the image is static. We call this kind of illusion art as “Self-animating images (SAIs)”.
Figure 1. Rotating snakes [1]

In the past, many scientists have attempted to understand illusory motion by using some simple, repeated asymmetric color patterns (RAP) [2] and found several useful rules to enhance its strength. In their study, some typical RAP patterns are the combinations of black, white and gray to study illusory motion and later only a few color patterns including blue-yellow or red-green were added to their study. Usually, a single RAP does not produce strong motion and it is hard to perceive its motion direction as well. However, when many RAPs are placed together in a good manner, illusory motion can emerge

Illusion demonstration is indeed fun to view and is potentially useful for entertainment and advertising purpose. However, the illusion art is still not prevalent due to a limited choice of colors and simple geometric shapes. Most existing work is done manually and time consuming to create. There is no existing technique automatically converting a given image to a self-animating image. In this work, we are the first research team to propose a novel computational framework to create self-animating images. Based on existing psychological knowledge on illusory motion [3], our method automatically optimizes for the effect of illusory motion.

Figure 2 depicts an overview of our novel framework. First, the user inputs a color image and segmentation is executed on it. To better abstract the region shapes and to enhance the strength of the illusion effect, we design a vector field generation method to maximize opposite directional flow among regions. The step is optional if a vector field is provided by the user. We adopt a streamline technique to visualize the vector field. To generate illusion, we place RAPs illusion patterns along the streamlines. To further maximize illusion effect, we optimize the positions of RAPs on the streamlines. Finally, we design a novel scheme to determine the most illusive color combination according to the color of input image, and to colorize the RAPs to generate the self-animating image. This novel contribution allows the RAP color combinations from the limited color set to a wide range of color and makes SAIs more practical for illusion art.
Figure 2: An overview of generating a self-animating image [4].

With this novel research, our work can benefit many computer graphics applications such as non-photo-realistic rendering and static vector field visualization. Figures 3 and 4 show two examples produced by our system: an illusory SIGGRAPH logo and ocean visualization, respectively. More examples can be found in [4] and our project web site: http://graphics.csie.ncku.edu.tw/SAI/ . Finally, it is worth being mentioned that 1) our work is selected as one of four highlight papers from 518 ACM SIGGRAPH 2008 technical paper submissions and 2) a recent article (2008 Sept. Issue) [5] published at Newsweek/Russia reports our research (see Figure 5). 
Figure 3: Illusory SIGGRAPH logo [4]
Figure 4: An example of visualizing an ocean flow [4].

Illusory motion is still an open and challenging cross-disciplinary field of research. Currently, each individual perceives the strength of the illusion differently depending on the size of the RAP elements. Generally speaking, when these motion-inducing elements are too small, the evoked motion illusion vanishes. This can be easily verified, when looking at the same illusion pattern from a farther viewing distance. Therefore, it is very challenging to generate a self-animating image that is faithful to every single detail of the input image in near future.
Figure 5. A special report of our research at Newsweek/Russia [5]


[1] KITAOKA, A., 2003. Rotating snakes. http://www.psy.ritsumei.ac.jp/~akitaoka/rotsnakee.html .
[2] BACKUS, B. T., AND ORUC, I. 2005. Illusory motion from change over time in the response to contrast and luminance. J. Vis. 5, 11 (12), 1055–1069.
[3] KITAOKA, A. 2006. The effect of color on the optimized fraserwilcox illusion. the 9th L’ORE’AL Art and Science of Color Prize, 1–16.
[4] Ming-Te Chi, Tong-Yee Lee, Yingge Qu and Tien-Tsin Wong, " Self-Animating Images: Illusory Motion Using Repeated Asymmetric Patterns", ACM Transactions on Graphics (SIGGRAPH 2008 issue), Vol. 27, No. 3, August 2008, pp. 62:1-62:8.
[5] http://graphics.csie.ncku.edu.tw/SAI/illusia_newsweek_russia.pdf
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