The DOI matches its Crossref record.
Applications of Human Motion Tracking: Smart Lighting Control
Abstract
This paper presents a smart lighting control system based on human motion tracking. Proper illumination and color temperature depend on human activities. A smart lighting system that provides automatic control of lighting illumination and color temperature needs to track human motion and understand human activities. Infrared and thermal spectrum provides useful information robust to the lighting condition. Depth information can be acquired independently of the lighting condition and it is relatively easy to detect humans independent of their clothing, and skin color. Commercial depth cameras or thermal cameras were used for accurate tracking and for estimating human behavior. The activity modes can be estimated using the human motion tracking results from depth cameras and from thermal cameras. Multiple depth cameras were used to detect human subject motion in a large area. The activity modes such as study mode and watching TV mode were estimated and the illumination and color temperature of the LED lighting system were controlled in real time according to the estimated activity.
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“Chun and Lee [100] in their research said that ultrasonic sensors and PIR sensors estimate human location and function to turn on or turn off lights in smart lighting.”
From Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey (2022) · cites this paper as Chun and Lee [100]
Citations
Cites
No references could be resolved yet.
Research works printed but not linked: 7
- 10.1109/ICTC.2011.6082600 · DOI
- 10.1016/j.enbuild.2005.12.001 · DOI
- aldrich, 2010, Energy efficient control of polychromatic solid state lighting using a sensor network, Proc of SPIE, 7784, 10.1117/12.860755 · DOI
- wen, 2008, Energy conservation utilizing wireless dimmable lighting control in a sharedspace office, Illuminating Eng Soc Annu Conf
- 10.1117/2.1201102.003543 · DOI
- oi, 2007, Preferred combinations between illuminance and color temperature in several settings for daily living activities, Proc of International Symposium on Design of Artificial Environments, 214
- 10.1109/CDC.2009.5400442 · DOI
Cited by
Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey
Putrada, A. G., Abdurohman, M., Perdana, D., & Nuha, H. H. (2022) · IEEE Access · doi:10.1109/access.2022.3169765 · Cited by 101
“Chun et al. [100] in their research said that ultrasonic sensors and PIR sensors estimate human location and function to turn on or turn off lights in smart lighting.”
Background
Metadata
- Authors
- Chun, S. Y., & Lee, C.-S.
- Affiliations
- Yeungnam University (KR)
- ORCID
- Lee, Chan-Su
- Venue
- 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops
- Publisher
- IEEE
- Published
- 2013-06
- Pages
- 387-392
- OpenAlex
- W1995121136
- Cited by
- 28
- References
- 0
- Citations by year
- 2026: 2 · 2024: 1 · 2023: 4 · 2022: 3 · 2021: 3 · 2020: 2 · 2019: 5 · 2018: 3 · 2016: 2 · 2015: 3
- FWCI
- 1.06
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Physical Sciences › Engineering › Building and Construction › Building Energy and Comfort Optimization
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
- Keywords
- human motion tracking, intelligent lighting control, activity recognition, depth camera, thermal camera, infrared detection, color temperature control, LED lighting, multi-camera tracking, human detection, study mode
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