Abstract
Facial makeup significantly changes the perceived appearance of the face and reduces the accuracy of face recognition. To adapt to the application of smart cities, in this study, we introduce a novel joint subspace and low-rank coding method for makeup face recognition. To exploit more discriminative information of face images, we use the feature projection technology to find proper subspace and learn a discriminative dictionary in such subspace. In addition, we use a low-rank constraint in the dictionary learning. Then, we design a joint learning framework and use the iterative optimization strategy to obtain all parameters simultaneously. Experiments on real-world dataset achieve good performance and demonstrate the validity of the proposed method.
Highlights
Digital technology represented by artificial intelligence, Internet of things (IoT), and cloud computing, etc. is developing vigorously for smart cities
We develop a joint subspace and low-rank coding method for makeup face recognition (JSLC)
Similar results are obtained on histogram of oriented gradient (HOG) feature; JSLC obtains the best matching performance compared with the other four methods. e results in Tables 1–3 indicate that HOG, local binary patterns (LBP), and three-patch LBP (TPLBP) features are suitable for extracting makeup face feature vectors. e bold means the best result in the tables
Summary
Digital technology represented by artificial intelligence, Internet of things (IoT), and cloud computing, etc. is developing vigorously for smart cities. Artificial intelligence as a powerful tool provides intelligence for smart cities, and a large number of machine learning algorithms are put into practical application to realize the autonomy of the equipment, which completes data collection and processing by itself. In this case, artificial intelligence helps to collect relevant data, identify alternatives, and make choices among alternatives, review decisions, and make predictions [4, 5]. Candidates verify their identity through a face recognition system to ensure fairness and prevent the occurrence of test substitution
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
