ABSTRACT
This paper develops methods for determining a visually appealing length for a motion transition, i.e., a segue between two sequences of character animation. Motion transitions are an important component in generating compelling animation streams in virtual environments and computer games. For reasons of efficiency and speed, linear interpolation is often used as the transition method, where the motion is blended between specified start and end frames. The blend length of a transition using this technique is critical to the visual appearance of the motion. Two methods for determining an optimal blend length for such transitions are presented. These methods are suited to different types of motion. They are empirically evaluated through user studies. For the motions tested, we find (1) that visually pleasing transitions can be generated using our optimal blend lengths without further tuning of the blending parameters; and (2), that users prefer these methods over a generic fixed-length blend.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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2
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3
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4
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5
|
|
| |
6
|
{GS66} Green D. M., Swets J. A.: Signal Detection Theory and Psychophysics. John Wiley and Sons, New York, 1966.
|
 |
7
|
|
| |
8
|
|
| |
9
|
{Joh73} Johansson G.: Visual perception of biological motion and a model for its analysis. Perception and Psychophysics 14 (1973), 201--211.
|
| |
10
|
|
 |
11
|
|
 |
12
|
|
 |
13
|
|
| |
14
|
|
| |
15
|
{MBC01} Mizuguchi M., Buchanan J., Calvert T.: Data driven motion transitions for interactive games. Eurographics 2001 Short Presentations (2001).
|
| |
16
|
{Md98} Michaels C. F., de Vries M. M.: Higher order and lower order variables in the visual perception of relative pulling force, Journal of Experimental Psychology: Human Perception and Performance 24, 2 (1998), 526--546.
|
 |
17
|
|
| |
18
|
{OHJ00} Oesker M., Hecht H., Jung B.: Psychological evidence for unconscious processing of detail in real-time animation of multiple characters. The Journal of Visualization and Computer Animation 11, 2 (June 2000), 105--112.
|
 |
19
|
|
| |
20
|
|
| |
21
|
{PPBS01} Pollick F., Paterson H. M., Bruderlin A., Sanford A. J.: Perceiving affect from arm movement. Cognition 82, 2 (2001), B51-B61.
|
| |
22
|
|
 |
23
|
|
| |
24
|
|
 |
25
|
|
| |
26
|
{Ric95} Rice J. A.: Mathematical Statistics and Data Analysis, 2nd ed. Duxbury Press, Belmont, CA, 1995.
|
 |
27
|
|
| |
28
|
|
| |
29
|
{SI87} Sogon S., Izard C. B.: Sex differences in emotion recognition by observing body movements. Psychological Research 29 (1987), 89--93.
|
| |
30
|
|
| |
31
|
|
 |
32
|
|
 |
33
|
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CITED BY 15
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David A. Forsyth , Okan Arikan , Leslie Ikemoto , James O'Brien , Deva Ramanan, Computational studies of human motion: part 1, tracking and motion synthesis, Foundations and Trends® in Computer Graphics and Vision, v.1 n.2, p.77-254, July 2006
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