Fast and Accurate Object Detection Based on Binary Co-occurrence Features
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- Ambai Mitsuru
- Denso IT Laboratory, Inc.
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- Kimura Taketo
- Denso IT Laboratory, Inc.
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- Sakai Chiori
- Denso IT Laboratory, Inc.
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説明
In this paper, we propose a fast and accurate object detection algorithm based on binary co-occurrence features. In our method, co-occurrences of all the possible pairs of binary elements in a block of binarized HOG are enumerated by logical operations, i.g. circular shift and XOR. This resulted in extremely fast co-occurrence extraction. Our experiments revealed that our method can process a VGA-size image at 64.6fps, that is two times faster than the camera frame rate (30fps), on only a single core of CPU (Intel Core i7-3820 3.60GHz), while at the same time achieving a higher classification accuracy than original (real-valued) HOG in the case of a pedestrian detection task.
収録刊行物
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- Information and Media Technologies
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Information and Media Technologies 10 (3), 464-467, 2015
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詳細情報 詳細情報について
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- CRID
- 1390001205264722944
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- NII論文ID
- 130005100023
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- ISSN
- 18810896
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可
