Identity recognition based on generalised linear regression classification for multi‐component images

2016 ◽  
Vol 10 (1) ◽  
pp. 18-27 ◽  
Author(s):  
Yang‐Ting Chou ◽  
Jar‐Ferr Yang
Keyword(s):  
Linear Regression ◽  
Identity Recognition ◽  
Linear Regression Classification

Double linear regression classification for face recognition

2014 ◽  
Vol 62 (4) ◽  
pp. 288-295 ◽  
Author(s):  
Qingxiang Feng ◽  
Qi Zhu ◽  
Lin-Lin Tang ◽  
Jeng-Shyang Pan
Keyword(s):  
Face Recognition ◽  
Linear Regression ◽  
Linear Regression Classification

MapReduce-Based Parallel Linear Regression for Face Recognition

2014 ◽  
Vol 556-562 ◽  
pp. 2628-2632 ◽  
Author(s):  
Li Sheng Zhang ◽  
Hua Yong Liu ◽  
Da Jiang Lei
Keyword(s):  
Face Recognition ◽  
Linear Regression ◽  
Time Complexity ◽  
Distance Measure ◽  
Classification Algorithm ◽  
Vector Subspace ◽  
Test Image ◽  
Original Response ◽  
Response Vector ◽  
Linear Regression Classification

In order to solve the problem of high time complexity of Linear Regression Classification algorithm,we propose a Mapreduce-based parallel linear regression classification algorithm. The map task uses the test image vector and the vector subspace to predict the response vector for one class, then calculates the distance measure between the predicted response vectory and the original response vector. The reduce task processes the data which are generated by the mappers, the test image is assigned to the nearest class. The experiments shows that the MapReduce-based parallel linear regression classifier can significantly improve the efficiency of Face Recognition.

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