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Table 2 Computation complexity comparisons

From: Efficient face detection method with eye region judgment

Operation number Method
  Traditional Adaboost face detector with Haar-like features The hybrid Adaboost-based face detector of PFMPF and PBHFA Proposed system
Addition/subtraction (suppose a detection window of size N × N) Integral image 3 × N × N PFMPF N × N JEER for PFMPF Less than (N × N) + 0.1(N × N)
K weak classifier 7 × K (suppose all the K weak classifiers are two-rectangle features) PBH feature Less than 2 × N × N JEER for PBH feature Less than (2 × N × N) + 0.1(N × N)
Addition/subtraction (suppose a detection window of size 24 × 24) Case 1: 1,847 operations (suppose 17 weak classifiers are two-rectangle features) 85% of images use 576 operations, and 15% of images use less than 1,728 operations 91% of images use 633 operations, and 9% of images use less than 1,843 operations
  Case 2: >1,847 operations (suppose three-rectangle or four-rectangle features are used)     
  1. Comparisons among the proposed system, the hybrid Adaboost-based face detector of PFMPF and PBHFA, and the traditional Adaboost face detection system that uses the Haar-like features.