caa a22 4500 606160175 CHVBK 20210128100628.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s00521-014-1803-x doi (NATIONALLICENCE)springer-10.1007/s00521-014-1803-x Fast and accurate face detection by sparse Bayesian extreme learning machine [Elektronische Daten] [Chi Vong, Keng Tai, Chi Pun, Pak Wong] Real-time face detection is an important research topic in computer vision and pattern recognition. One of the effective methods in face detection is model-based approach which employs neural network technique for the construction of classification model. Relevant techniques such as support vector machines are fast in training an accurate model which is, however, relatively slow in execution time. The reason is due to the large size of the constructed model. In this paper, the main contribution is to apply a new method called sparse Bayesian extreme learning machine (SBELM) for real-time face detection because SBELM can minimize the model size with nearly no compromise on the accuracy and have fast execution time. Several benchmark face datasets were employed for the evaluation of SBELM against other state-of-the-art techniques. Experimental results show that SBELM achieves fastest execution time with high accuracy over the benchmark face datasets. A MATLAB toolbox of SBELM is also available on our Web site. The Natural Computing Applications Forum, 2014 Face recognition nationallicence Face detection nationallicence Sparse Bayesian nationallicence Extreme learning machine nationallicence Vong Chi Department of Computer and Information Science, University of Macau, Macau, SAR, China aut Tai Keng Department of Computer and Information Science, University of Macau, Macau, SAR, China aut Pun Chi Department of Computer and Information Science, University of Macau, Macau, SAR, China aut Wong Pak Department of Electromechanical Engineering, University of Macau, Macau, SAR, China aut Neural Computing and Applications Springer London 26/5(2015-07-01), 1149-1156 0941-0643 26:5<1149 2015 26 521 https://doi.org/10.1007/s00521-014-1803-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-014-1803-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Vong Chi Department of Computer and Information Science, University of Macau, Macau, SAR, China aut NATIONALLICENCE 700 1- Tai Keng Department of Computer and Information Science, University of Macau, Macau, SAR, China aut NATIONALLICENCE 700 1- Pun Chi Department of Computer and Information Science, University of Macau, Macau, SAR, China aut NATIONALLICENCE 700 1- Wong Pak Department of Electromechanical Engineering, University of Macau, Macau, SAR, China aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/5(2015-07-01), 1149-1156 0941-0643 26:5<1149 2015 26 521