A survey of face recognition techniques

TL;DR: This paper discusses how HFR can be implemented using SIFT and MLBP algorithm to extract various image features from heterogeneous images that help to give a correct match between probe and gallery images.

TL;DR: Experimental results show that MRLR beats several state-of-the-art approaches in terms of efficiency and scalability with comparable performance, and takes advantage of the block matrix inverse to develop an efficient solving algorithm whose efficiency and Scalability are verified by computational complexity analysis.

TL;DR: This paper proposed the mobile face recognition using data mining technique system which is able to help the police to find the suspects from the crime database using Smartphones.

TL;DR: The experimental results show that the use of subset 1 images as training data turns out to produce the lowest facial recognition performance where the accuracy is 90.00%.

TL;DR: A comprehensive review of the recent developments on deep face recognition can be found in this paper, covering broad topics on algorithm designs, databases, protocols, and application scenes, as well as the technical challenges and several promising directions.

TL;DR: This research highlights the existing technologies of listening, speaking, reading, writing, and other senses, which are widely used in human interaction, and introduces some intelligent robot systems and platforms.

TL;DR: This paper presents comparison concerning various biometric systems simply by defining their advantages and disadvantages, restricted to accuracy, size of template, cost, security level, and long term stability.

TL;DR: A comparison of representative thermal face recognition methods is given, emphasizing their strengths and weaknesses, and trends in the development of surveillance and security systems will be outlined such as fusion of visible and thermal images and use of convolutional neural networks.