Title :
Digital movies using optimized feature maps
Author :
Matsuyama, Yasuo ; Tan, Masayoshi
Author_Institution :
Dept. of Comput. & Inf. Sci., Ibaraki Univ., Hitachi, Japan
fDate :
27 Jun- 2 Jul 1994
Abstract :
Steps from DC (data compression) to AC (animation coding) are discussed. This means that a digital movie is generated from a single still image using data compression. Such processing is made possible by the multiply optimized competitive learning (multiply descent cost competitive learning). A key point is the usage of the optimized feature map. This optimized feature map groups nearby pixels together. Therefore, it is also called grouping feature map. Since this grouping feature map is optimized with respect to the source image and standard weight vectors, it possesses the ability of source data recovery. This property can not be realized by plain feature maps. The grouping feature map and standard weight vectors are metamorphic. Given information to move vertices in the grouping feature map, modified images can be produced. Thus, by generating temporal key frames, digital movies are realized. An initial trial toward 3D image processing is also given
Keywords :
computer animation; data compression; image coding; self-organising feature maps; unsupervised learning; 3D image processing; animation coding; data compression; digital movies; multiply descent cost competitive learning; multiply optimized competitive learning; optimized feature maps; Animation; Communication cables; Cost function; Data compression; Image coding; Image generation; Image processing; Information processing; Interpolation; Motion pictures;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374853