Optimization-Based Multi-view Head Pose Estimation for Driver Behavior Analysis

摘要

An optimization-based multi-view head pose estimation method is presented, it takes advantage of the constraint relationship formed by the relative positions of the cameras and the driver's head to fuse multiple estimation results and generate an optimized solution. The proposed method is novel in the following ways: 1. it introduces the ideal pose constraint conditions for each view pose self-adjustment, 2. it sets up the optimization goal of minimizing the average of the 3D projection error in the 2D plane to guide pose estimated value adjustment, and 3. it determines the adjustment through the iteration process for each view pose. The proposed method can improve the accuracy and confidence of the system estimation, which has been verified by simulation and real measurement.