Yann-Aël Le Borgne
ABSTRACT
The Principal Component Aggregation has recently been proposed as a versatile distributed information extraction technique for sensor networks [3]. This demonstration illustrates its use for a network-level pattern recognition task. Four different patterns, or events, may be sensed by light measurements of a network of 27 nodes. The sens measurements are fused on the fly along a routing tree up to the base station, where the monitored pattern is recognized by a prediction algorithm.
- J. Friedman, T. Hastie, and R. Tibshirani. The elements of statistical learning, 2001.Google Scholar
- C. Intanagonwiwat, R. Govindan, and D. Estrin. Directed diffusion: A scalable and robust communication paradigm for sensor networks. In Proceedings of the 6th annual international conference on Mobile computing and networking, pages 56--67. ACM New York, NY, USA, 2000. Google ScholarDigital Library
- Y. Le Borgne, J. Dricot, and G. Bontempi. Principal Component Aggregation for Energy-efficient Information Extraction in Wireless Sensor Networks, chapter 5, pages 55--80. Taylor and Francis/CRC Press, 2008.Google Scholar
- S. Madden, M. Franklin, J. Hellerstein, and W. Hong. TinyDB: an acquisitional query processing system for sensor networks. ACM Transactions on Database Systems, 30(1):122--173, 2005. Google ScholarDigital Library
- Wireless Sensor Lab. University of Brussels. http://www.ulb.ac.be/di/labo/index.html.Google Scholar
Index Terms
- Demonstrating principal component aggregation for distributed spatial pattern recognition
Recommendations
Recognition of Faces Using Improved Principal Component Analysis
ICMLC '10: Proceedings of the 2010 Second International Conference on Machine Learning and ComputingFace recognition has been an important issue in computer vision and pattern recognition over the last several decades. While a human can recognize faces easily, automated face recognition remains a great challenge in computer-based automated recognition ...
Coupled principal component analysis based face recognition in heterogeneous sensor networks
In this paper, we construct heterogeneous sensor networks (HSN) for face recognition and propose a novel approach named coupled principal component analysis (CPCA) that uses a feature-based representation for heterogeneous face images. We first employ ...
An Analysis on Face Recognition using Principal Component Analysis Approach
ICIGP '22: Proceedings of the 2022 5th International Conference on Image and Graphics ProcessingFace recognition is a type of biometric recognition based on human facial feature information. Human face images or videos can be automatically collected using a high definition camera. Advanced technologies then can be used for face recognition by ...
Comments