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首页> 外文会议>IAPR TC3 Workshop on pattern recognition of social signals in human-computer-interaction >Face Recognition in Home Security System Using Tensor Decomposition Based on Radix-(2 X 2) Hierarchical SVD
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Face Recognition in Home Security System Using Tensor Decomposition Based on Radix-(2 X 2) Hierarchical SVD

机译：基于Radix-（2 X 2）分层SVD的张量分解的家庭安全系统中的人脸识别

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This paper explains research based on improving real time face recognition system using new Radix-(2 × 2) Hierarchical Singular Value Decomposition (HSVD) for 3~(rd) order tensor. The scientific interest, aimed at the processing of image sequences represented as tensors, was significantly increased in the last years. Current home security solutions can be cost-prohibitive, prone to false alarms, and fail to alert the user of a break-in while they are away from the home. Because of advancements in facial detection and recognition techniques made in the past decade, we propose a home security system that takes advantage of this technology. To create such a system at a low cost requires algorithms that are powerful enough to detect users in various environmental conditions and fast enough to process real time video on weaker hardware. Experiments comparing the efficiency of two different decomposition techniques applied for face recognition in real time.
机译：本文解释了基于改进的实时人脸识别系统的研究，该系统使用新的Radix-（2×2）分层奇异值分解（HSVD）来处理3〜（rd）张量。近年来，针对处理以张量表示的图像序列的科学兴趣显着增加。当前的家庭安全解决方案可能是成本过高的，容易产生误报，并且在他们离开家时无法向用户发出闯入警报。由于过去十年中面部检测和识别技术的进步，我们提出了一种利用该技术的家庭安全系统。为了以低成本创建这样的系统，需要有足够强大的算法来检测各种环境条件下的用户，并且要有足够快的算法来在较弱的硬件上处理实时视频。实验比较了两种实时应用于人脸识别的不同分解技术的效率。

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