Occupant-aware indoor monitoring for enhanced building analysis
Abstract
In this paper a novel, cost-effective and robust occupancy monitoring system is presented, which is based on a fuzzy confidence voting algorithm utilizing spatial height histograms. Spatial height histograms are invariant to rotations and translations, providing this way a desirable feature to occupancy measurement systems, and when combined with distance coefficients can fix an occupancy feature vector, which is the main source for the fuzzy confidence voting occupant tracking algorithm. The proposed occupancy extraction system can be efficiently applied to multi-space environments using a privacy preserving multi-camera cloud. Statistics per building, space and occupant can be finally extracted by the system. The experimental results will illustrate its robustness, accuracy and efficiency on occupancy extraction.
References
[1]
Bernardin, K., and Stiefelhagen, R. Evaluating multiple object tracking performance: The clear mot metrics. Journal on Image and Video Processing (2008).
[2]
Besag, J. On the statistical analysis of dirty pictures. Journal of the Royal Statistical Society 48, 3 (1986), 259--302.
[3]
Beymer, D. Person counting using stereo. In Workshop on Human Motion (2000), 127--133.
[4]
Black, J., Ellis, T., and Rosin, P. Multi-view image surveillance and tracking. In IEEE Workshop on Motion and Video Computing (2002).
[5]
Brscic, D., Kanda, T., Ikeda, T., and Miyashita, T. Person tracking in large public spaces using 3-d range sensors. IEEE Transactions Human-Machine Systems 43, 6 (2013), 522--534.
[6]
Charreyron, S., Jackson, S., and Miranda-Moreno, L. Toward a flexible system for pedestrian data collection with a microsoft kinect motion-sensing device. Journal of the Transportation Research Board 2 (2014), 80--89.
[7]
Comaniciu, D., Ramesh, V., and Meer, P. Kernel-based object tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence 25, 5 (2003), 564--575.
[8]
Focken, D., and Stiefelhagen, R. Towards vision-based 3d people tracking in a smart room. In IEEE International Conference on Multimodal Interfaces (2002).
[9]
Ioannidis, D., Tzovaras, D., and Malavazos, C. Occupancy and business modelling. In 9th European Conference on Product and Process Modelling (ECPPM'12), 3rd Workshop on eeBDM (2013).
[10]
Kang, J., Cohen, I., and Medioni, G. Tracking people in crowded scenes across multiple cameras. In Proceedings of Asian Conference on Computer Vision (2004).
[11]
Krinidis, S., and Chatzis, V. A robust fuzzy local information c-means clustring algorithm. IEEE Transactions on Image Processing 19, 5 (May 2010), 1328--1337.
[12]
Krinidis, S., Stavropoulos, G., Ioannidis, D., and Tzovaras, D. A robust and real-time multi-space occupancy extraction system exploiting privacy-preserving sensors. In Int. Symp. on Communications, Control and Signal Proc. (2014).
[13]
Mikic, I., Santini, S., and Jain, R. Video processing and integration from multiple cameras. In Image Understanding Workshop (1998).
[14]
Mittal, A., and Davis, L. M2tracker: A multi-view approach to segmenting and tracking people in a cluttered scene. International Journal of Computer Vision 51, 3 (2003), 189--203.
[15]
Otsuka, K., and Mukawa, N. Multi-view occlusion analysis for tracking densely populated objects based on 2Dvisual angles. In Conference on Computer Vision and Pattern Recognition (CVPR'04) (2004).
[16]
Ryu, H., and Huber, M. A particle filter approach for multi-target tracking. In International Conference on Intelligent Robots and Systems (2007), 2753--2760.
[17]
Salih, Y., and Malik, A. 3D tracking using particle filters. In IEEE Instrumentation and Measurement Technology Conference (2011), 1--4.
[18]
Yang, D., Gonzales-Banos, H., and Guibas, L. Counting people in crowds with a real-time network of simple image sensors. In International Conference on Computer Vision (2003), 122--129.
Index Terms
- Occupant-aware indoor monitoring for enhanced building analysis
Recommendations
A video-based indoor occupant detection and localization algorithm for smart buildings
ICIC'09: Proceedings of the 5th international conference on Emerging intelligent computing technology and applicationsIn buildings, a practical sensing system to collect occupant location information has great importance in improving occupants' comfort and utilizing energy more efficiently by optimizing control strategies of lighting, HVAC devices and elevators. We ...
Self-calibration of omnidirectional multi-cameras including synchronization and rolling shutter
Deal with consumer 360 cameras and spherical cameras without a privileged direction.Initialize the time offsets and intrinsic parameters using monocular structure-from-motion.Start multi-camera structure-from-motion with central and global shutter ...
Assessing a multi-camera system to enhance fruit visibility for robotic harvesting in a V-trellised apple orchard
AbstractAccurate detection and localization of fruits within the canopy are crucial for various tasks, such as perception for robotic harvesters, vision-based yield estimation, and early disease detection. However, complex canopy structures render fruit ...
Highlights- Multi-camera systems enhance visibility in V-shaped canopies.
- A single camera detected up to 88.3% of apples compared to four cameras.
- Two cameras detected up to 97.5% of apples compared to four cameras.
- Four cameras show ...
Comments
Information & Contributors
Information
Published In
Sponsors
- SIGSIM: ACM Special Interest Group on Simulation and Modeling
- SCS: Society for Modeling and Simulation International
Publisher
Society for Computer Simulation International
San Diego, CA, United States
Publication History
Published: 12 April 2015
Check for updates
Author Tags
Qualifiers
- Research-article
Conference
SpringSim '15
Sponsor:
- SIGSIM
- SCS
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 38Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 17 Feb 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in