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As many objects in the human ambient environment are intellectualized and  networked, research on IoT technology have increased to improve the quality  of human life. This paper suggests an LDA-based long distance face  recognition algorithm to enhance the intelligent IoT interface. While the  existing face recognition algorithm uses single distance image as training  images, the proposed algorithm uses face images at distance extracted from 1m  to 5m as training images. In the proposed LDA-based long distance face  recognition algorithm, the bilinear interpolation is used to normalize the  size of the face image and a Euclidean Distance measure is used for the  similarity measure. As a result, the proposed face recognition algorithm is  improved in its performance by 6.1% at short distance and 31.0% at long  distance, so it is expected to be applicable for USN’s robot and surveillance  security systems.

Long distance face recognition for enhanced performance of internet of things service interface