Corner Feature Detection Based on Discrete Spherical Model

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概要

• 論文の詳細を見る

• This paper proposes a method of finding scale-invariant corner feature from full-view image based on discrete spherical model. A full-view image is first mapped to a discrete spherical image. Then, Harris corners are detected in the discrete spherical image. After determining the scale of the found corner points, the descriptor of corner feature is generated from the patch determined by the position and the scale. In comparison with detecting feature from the full-view image directly, the proposed method can find more stable features and achieves higher rate of feature matching for full-view image pairs independent of the feature position at image.

• 信号処理学会の論文

信号処理学会 | 論文

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