Grid Sample Based Temporal Iteration for Fully Pipelined 1-ms SLIC Superpixel Segmentation System
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- LI Yuan
- Graduate School of Information, Production and Systems, Waseda University
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- HU Tingting
- Panasonic Connect Co., Ltd.
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- FUCHIKAMI Ryuji
- Panasonic Connect Co., Ltd.
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- IKENAGA Takeshi
- Graduate School of Information, Production and Systems, Waseda University
抄録
<p>A 1 millisecond (1-ms) vision system, which processes videos at 1000 frames per second (FPS) within 1ms/frame delay, plays an increasingly important role in fields such as robotics and factory automation. Superpixel as one of the most extensively employed image oversegmentation methods is a crucial pre-processing step for reducing computations in various computer vision applications. Among the different superpixel methods, simple linear iterative clustering (SLIC) has gained widespread adoption due to its simplicity, effectiveness, and computational efficiency. However, the iterative assignment and update steps in SLIC make it challenging to achieve high processing speed. To address this limitation and develop a SLIC superpixel segmentation system with a 1ms delay, this paper proposes grid sample based temporal iteration. By leveraging the high frame rate of the input video, the proposed method distributes the iterations into the temporal domain, ensuring that the system's delay keeps within one frame. Additionally, grid sample information is added as initialization information to the obtained superpixel centers for enhancing the stability of superpixels. Furthermore, a selective label propagation based pipeline architecture is proposed for parallel computation of all the possibilities of label propagation. This eliminates data dependency between adjacent pixels and enables a fully pipelined system. The evaluation results demonstrate that the proposed superpixel segmentation system achieves boundary recall and under-segmentation error comparable to the original SLIC algorithm. When considering label consistency, the proposed system surpasses the performance of state-of-the-art superpixel segmentation methods. Moreover, in terms of hardware performance, the proposed system processes 1000FPS images with 0.985ms/frame delay.</p>
収録刊行物
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- IEICE Transactions on Information and Systems
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IEICE Transactions on Information and Systems E107.D (4), 515-524, 2024-04-01
一般社団法人 電子情報通信学会
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詳細情報 詳細情報について
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- CRID
- 1390862623772247680
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- ISSN
- 17451361
- 09168532
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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
- Crossref
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- 抄録ライセンスフラグ
- 使用不可