Total absolute Gaussian curvature for stereo prior

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

In spite of the great progress in stereo matching algorithms, the prior models they use, i.e., the assumptions about the probability to see each possible surface, have not changed much in three decades. Here, we introduce a novel prior model motivated by psychophysical experiments. It is based on minimizing the total sum of the absolute value of the Gaussian curvature over the disparity surface. Intuitively, it is similar to rolling and bending a flexible paper to fit to the stereo surface, whereas the conventional prior is more akin to spanning a soap film. Through controlled experiments, we show that the new prior outperforms the conventional models, when compared in the equal setting.

本文言語English
ホスト出版物のタイトルComputer Vision - ACCV 2007 - 8th Asian Conference on Computer Vision, Proceedings
出版社Springer Verlag
ページ537-548
ページ数12
PART 2
ISBN(印刷版)9783540763895
DOI
出版ステータスPublished - 2007 1 1
外部発表はい
イベント8th Asian Conference on Computer Vision, ACCV 2007 - Tokyo, Japan
継続期間: 2007 11 182007 11 22

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
番号PART 2
4844 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference8th Asian Conference on Computer Vision, ACCV 2007
CountryJapan
CityTokyo
Period07/11/1807/11/22

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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