Name
Title | ||
|---|---|---|
5.9 A 0.8V Multimode Vision Sensor for Motion and Saliency Detection with Ping-Pong PWM Pixel |
Abstract | ||
|---|---|---|
Energy-efficient always-on motion-detection (MD) sensors are in high demand and are widely used in machine vision applications. To achieve real-time and continuous motion monitoring, high-speed low-power temporal difference imagers with corresponding processing architectures are widely investigated [1-6]. Event-based dynamic vision sensors (DVS) have been reported to reduce the redundant data and power through the asynchronous timestamped event-address readout [1], [2]. However, DVS needs special data processing to collect enough events for information extraction, and suffers from noise and dynamic effects, which limits the advantages of low-latency pixel event reporting. Furthermore, low sensitivity (no integration) and lack of static information are also drawbacks of DVS. Frame-based MD rolling-shutter sensors [3], [4] were reported to reduce the data bandwidth and power by sub-sampling operation with the tradeoff of low resolution and motion blur. Global-shutter MD sensors were reported [5], [6] using in-pixel analog memory for reference image storage. However, such sensors require a special process technology for low off-state current device implementation. In a frame-based MD sensor, the required analog processing circuit and two successive frames for temporal difference operation comes at a cost in power, area, and speed. To address these drawbacks, we present a frame-based MD vision sensor featuring three operation modes: image-capture (IC), frame-difference (FD) with on/off event detection, and saliency-detection (SD). Using a low-voltage ping-pong PWM pixel and multi-mode operation, it achieves high-speed low-power full-resolution MD, consecutive event frame reporting, and image capture functions. Moreover, saliency detection by counting the block-level event number is also implemented for efficient optic flow extraction of the companion processing chip using simple neuromorphic circuits. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ISSCC19947.2020.9062926 | 2020 IEEE International Solid- State Circuits Conference - (ISSCC) |
Keywords | DocType | ISSN |
global-shutter MD sensors,in-pixel analog memory,reference image storage,off-state current device implementation,frame-based MD sensor,analog processing circuit,temporal difference operation,frame-based MD vision sensor,event detection,low-voltage ping-pong PWM pixel,multimode operation,full-resolution MD,image capture functions,saliency detection,block-level event number,motion-detection sensors,machine vision applications,continuous motion monitoring,high-speed low-power temporal difference imagers,event-based dynamic vision sensors,DVS,asynchronous timestamped event-address readout,data processing,information extraction,low-latency pixel event reporting,rolling-shutter sensors,subsampling operation,motion blurring,multimode vision sensor,optic flow extraction,SD,neuromorphic circuits,current 5.9 A,voltage 0.8 V | Conference | 0193-6530 |
ISBN | Citations | PageRank |
978-1-7281-3206-8 | 0 | 0.34 |
References | Authors | |
0 | 13 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tzu-Hsiang Hsu | 1 | 12 | 4.74 |
| Yen-kai Chen | 2 | 2 | 1.73 |
| Jun-Shen Wu | 3 | 0 | 1.01 |
| Wen-Chien Ting | 4 | 14 | 1.94 |
| Cheng-Te Wang | 5 | 1 | 2.07 |
| Chen-Fu Yeh | 6 | 0 | 1.01 |
| Syuan-Hao Sie | 7 | 1 | 0.69 |
| Yi-Ren Chen | 8 | 8 | 3.98 |
| Ren-Shuo Liu | 9 | 141 | 9.86 |
| Chung-Chuan Lo | 10 | 15 | 7.24 |
| Kea-Tiong Tang | 11 | 109 | 28.91 |
| Meng-Fan Chang | 12 | 459 | 45.63 |
| Chih-Cheng Hsieh | 13 | 218 | 44.84 |