An O(m+n)-Space Spatiotemporal Denoising Filter with Cache-Like Memories for Dynamic Vision Sensors
Dynamic vision sensor (DVS) is novel neuromorphic imaging device that generates asynchronous events. Despite the high temporal resolution and high dynamic range features, DVS is faced with background noise problem. Spatiotemporal filter is an effective and hardware-friendly solution for DVS denoisin...
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| Veröffentlicht in: | Digest of technical papers - IEEE/ACM International Conference on Computer-Aided Design S. 1 - 9 |
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| Abstract | Dynamic vision sensor (DVS) is novel neuromorphic imaging device that generates asynchronous events. Despite the high temporal resolution and high dynamic range features, DVS is faced with background noise problem. Spatiotemporal filter is an effective and hardware-friendly solution for DVS denoising but previous designs have large memory overhead or degraded performance issues. In this paper, we present a lightweight and real-time spatiotemporal denoising filter with set-associative cache-like memories, which has low space complexity of O(m+n) for DVS of m \times n resolution. A two-stage pipeline for memory access with read cancellation feature is proposed to reduce power consumption. Further the bitwidth redundancy for event storage is exploited to minimize the memory footprint. We implemented our design on FPGA and experimental results show that it achieves state-of-the-art performance compared with previous spatiotemporal filters while maintaining low resource utilization and low power consumption of about 125mW to 210mW at 100MHz clock frequency. |
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| AbstractList | Dynamic vision sensor (DVS) is novel neuromorphic imaging device that generates asynchronous events. Despite the high temporal resolution and high dynamic range features, DVS is faced with background noise problem. Spatiotemporal filter is an effective and hardware-friendly solution for DVS denoising but previous designs have large memory overhead or degraded performance issues. In this paper, we present a lightweight and real-time spatiotemporal denoising filter with set-associative cache-like memories, which has low space complexity of O(m+n) for DVS of m \times n resolution. A two-stage pipeline for memory access with read cancellation feature is proposed to reduce power consumption. Further the bitwidth redundancy for event storage is exploited to minimize the memory footprint. We implemented our design on FPGA and experimental results show that it achieves state-of-the-art performance compared with previous spatiotemporal filters while maintaining low resource utilization and low power consumption of about 125mW to 210mW at 100MHz clock frequency. |
| Author | Shi, Guangming Wu, Jinjian Ji, Yixi Zhao, Qinghang Wang, Jiaqi |
| Author_xml | – sequence: 1 givenname: Qinghang surname: Zhao fullname: Zhao, Qinghang email: qhzhao@xidian.edu.cn organization: Xidian University,China – sequence: 2 givenname: Jiaqi surname: Wang fullname: Wang, Jiaqi organization: Xidian University,China – sequence: 3 givenname: Yixi surname: Ji fullname: Ji, Yixi organization: Xidian University,China – sequence: 4 givenname: Jinjian surname: Wu fullname: Wu, Jinjian organization: Xidian University,China – sequence: 5 givenname: Guangming surname: Shi fullname: Shi, Guangming organization: Xidian University,China |
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| Snippet | Dynamic vision sensor (DVS) is novel neuromorphic imaging device that generates asynchronous events. Despite the high temporal resolution and high dynamic... |
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| SubjectTerms | Denoising Dynamic Vision Sensor Field programmable gate arrays FPGA Memory architecture Memory management Noise reduction Pipeline processing Power demand Real-time systems Spatiotemporal Filter Spatiotemporal phenomena Vision sensors Voltage control |
| Title | An O(m+n)-Space Spatiotemporal Denoising Filter with Cache-Like Memories for Dynamic Vision Sensors |
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