Name
Abstract | ||
|---|---|---|
This paper presents a novel computational imaging method for object tracking. The proposed slit-type one-dimensional brightness distribution sensor (Obrid-Sensor) is designed to be applied to detect falls, localize, and track subjects without invading privacy. According to the vertical and horizontal one-dimensional brightness distributions acquired by the proposed sensors, the subject's motion is monitored without images or videos. The effectiveness of the proposed method to detect falls, localize, and track is verified by experiment. The motion detection and location can be implemented without requiring images or videos, which may invade privacy. The detection range of the proposed privacy-preserving sensor is also confirmed. Finally, the proposed sensor has a simpler structure than the traditional Obrid-Sensor, making it attractive owing to its simple design, facile application, and low cost. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.compeleceng.2016.09.023 | Computers & Electrical Engineering |
Keywords | Field | DocType |
Obrid-Sensor,Brightness distribution,Computational imaging,Safety confirmation,Object tracking | Computer vision,Motion detection,Computer science,Computational photography,Real-time computing,Video tracking,Artificial intelligence,Slit,Brightness | Journal |
Volume | Issue | ISSN |
58 | C | 0045-7906 |
Citations | PageRank | References |
1 | 0.37 | 2 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shota Nakashima | 1 | 54 | 11.05 |
| Shenglin Mu | 2 | 45 | 6.74 |
| Shingo Aramaki | 3 | 1 | 1.05 |
| Yuhki Kitazono | 4 | 5 | 5.13 |
| Kanya Tanaka | 5 | 18 | 12.75 |