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Description:To reduce the impact of adverse local changes e. However, the range of variation of different facial parts is still a challenge. GLVQ is based on a neural network and is not easily fooled by attempts to conceal identity via the usage of caps, hats, sunglasses, etc. GLVQ based multiple-matching face detection Combination of eye-zone extraction and facial recognition Recognition based on neural network technology Short processing time, high recognition rate Recognition regardless of vantage point and facial changes glasses, beard, and expression Reliable matching Optimal results through Adaptive Regional Blend Matching ARBM technology Extraction of similar facial areas Identification and authentication based on individual facial features Easy adaptation to existing IT systems Flexible integration into many types of video monitoring systems 1: The minimization of the local changes guarantees the overall face recognition accuracy. The three-dimensional representations of the head are then rotated in both the left-to-right and up-and-down directions.