- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
[IEEE 2018 IEEE International Conference on Electro/Information Technology (EIT) - Rochester, MI (2018.5.3-2018.5.5)] 2018 IEEE International Conference on Electro/Information Technology (EIT) - Evaluation of Indoor Positioning Technologies for Prototyping at Kettering University
摘要： This paper presents research performed on indoor positioning technologies to identify a technology that would be best to implement in a prototype at Kettering University’s campus. The indoor positioning techniques evaluated are mainly based including Bluetooth, Wi-Fi, Geomagnetic, Visual Light Communication (VLC), and Ultra- Wideband (UW). Target-side wearable sensors will be considered. The algorithms commonly used for calculating the user’s position will be discussed, including Trilateration, Fingerprinting, and K- Nearest-Neighbor.
关键词： Visual Light Communication,Ultra-Wideband,Geomagnetic,Trilateration,K-nearest-neighbor,Fingerprinting,Indoor Positioning System,Wi-Fi,Bluetooth
更新于2025-09-09 09:28:46
-
Face Recognition System Based on Spectral Graph Wavelet Theory
摘要： This study presents an efficient approach for automatic face recognition based on Spectral Graph Wavelet Theory (SGWT). SGWT is analogous to wavelet transform and the transform functions are defined on the vertices of a weighted graph. The given face image is decomposed by SGWT at first. The energies of obtained sub-bands are fused together and considered as feature vector for the corresponding image. The performance of proposed system is analyzed on ORL face database using nearest neighbor classifier. The face images used in this study has variations in pose, expression and facial details. The results indicate that the proposed system based on SGWT is better than wavelet transform and 94% recognition accuracy is achieved.
关键词： face recognition,spectral graph wavelet theory,Chebyshev polynomial,nearest neighbor classifier
更新于2025-09-09 09:28:46
-
[IEEE 2018 10th International Conference on Wireless Communications and Signal Processing (WCSP) - Hangzhou, China (2018.10.18-2018.10.20)] 2018 10th International Conference on Wireless Communications and Signal Processing (WCSP) - Vital Sign Integrated Tracking by Predictive KNN and Kalman Filter with UWB Radars
摘要： Ultra-wideband (UWB) radar is an effective tool for indoor tracking. By applying multiple radars in tracking, distance observations are obtained in different positions and the surveillance area is enlarged. However, even based on multiple radars, occlusions among targets still exist and cause loss of distance observations. Besides, imprecise initial positions introduce interferences at the beginning of tracking. This paper proposes a tracking approach to solve the problems. Firstly, the proposed approach integrates vital signs for target matching and provides precise initial positions for multiple targets tracking. Secondly, the proposed approach designs a predictive K-Nearest Neighbor method in both the raging stage and the data fusion stage, so as to reduce deviations in antenna-to-target distances and supplement the lost data. Experiments validate the effectiveness of the proposed approach in tracking multiple targets with a max average deviation 0.276m.
关键词： predictive K-Nearest Neighbor,UWB Radars,tracking,vital signs
更新于2025-09-04 15:30:14