An Improved Adaboost Method for Face Detection
2014 ◽
Vol 599-601
◽
pp. 807-813
Keyword(s):
Existing Adaboost methods for face detection based on particle swarm optimization (PSO) do not consider that PSO suffers from easily trapping in local optimum and slow convergence speed. This paper presents an improved Adaboost method for face detection to solve this problem. In this method, self-adaptive escape PSO (AEPSO) is introduced into conventional Adaboost face detection, meanwhile, Haar-Like rectangular features are represented by particles, so that features selection and classifiers construction could be resolved by using AEPSO. Results of simulation based on Matlab indicate the improved method obtains better detection performance.
2013 ◽
Vol 760-762
◽
pp. 2194-2198
◽
2013 ◽
Vol 427-429
◽
pp. 1934-1938
Keyword(s):
2017 ◽
Vol 40
(1)
◽
pp. 95-104