Digital movies using optimized feature maps

Yasuo Matsuyama*, Masayoshi Tan

*この研究の対応する著者

研究成果: Conference contribution

抄録

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.

本文言語English
ホスト出版物のタイトルIEEE International Conference on Neural Networks - Conference Proceedings
Place of PublicationPiscataway, NJ, United States
出版社IEEE
ページ4000-4005
ページ数6
6
出版ステータスPublished - 1994
外部発表はい
イベントProceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7) - Orlando, FL, USA
継続期間: 1994 6 271994 6 29

Other

OtherProceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7)
CityOrlando, FL, USA
Period94/6/2794/6/29

ASJC Scopus subject areas

  • ソフトウェア

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