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学术讲座:Sensor-assisted Face Recognition System on Smart Glass via Multi-view Sparse Representation Classification

阅读数:142    发布:2017-12-05 14:14    

报告题目:Sensor-assisted Face Recognition System on Smart Glass via Multi-view Sparse Representation Classification 

报告时间: 2017年12月6日 11:00 – 12:00 

报告地点: 计软大楼520 

报告人简介:Weitao Xu,澳大利亚昆士兰大学博士。他的研究兴趣集中于传感器网络,智能可穿戴设备,步态识别。他在相关领域顶级国际会议和期刊如IPSN,NDSS,TMC,TOSN发表若干论文并获得过相关会议最佳论文奖。他于2016年获得Google全球优秀博士奖学金(全球40人左右)。 

报告摘要:Face recognition is one of the most popular research problems on various platforms. New research issues arise when it comes to resource constrained devices, such as smart glasses, due to the overwhelming computation and energy requirements of the accurate face recognition methods. In this paper, we propose a robust and efficient sensor-assisted face recognition system on smart glasses by exploring the power of multimodal sensors including the camera and Inertial Measurement Unit (IMU) sensors. The system is based on a novel face recognition algorithm, namely Multi-view Sparse Representation Classification (MVSRC), by exploiting the prolific information among multi-view face images. To improve the efficiency of MVSRC on smart glasses, we propose a novel sampling optimization strategy using the less expensive inertial sensors. Our evaluations on public and private datasets show that the proposed method is up to 10% more accurate than the state-of-the-art multi-view face recognition methods while its computation cost is in the same order as an efficient benchmark method (e.g., Eigenfaces). Finally, extensive real-world experiments show that our proposed system improves recognition accuracy by up to 15% while achieving the same level of system overhead compared to the existing face recognition system (OpenCV algorithms) on smart glasses.


深圳大学计算机与软件学院 2009-2016