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Fusion algorithm of face detection and head
pose estimation based on SSD model |
School of Instrument Science and Engineering, Southeast University, Nanjing, Jiangsu 210096, China |
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Abstract To solve the problems of complex process, high coupling and low robustness in the twostep cascade framework of face detection and pose estimation in common head pose estimation, a fusion algorithm of face detection and head pose estimation was proposed based on the improved SSD model. By expanding the SSD model, a fusion network model of face detection and pose estimation was designed. Face was detected on multilevel convolution feature map, and head pose was estimated. Endtoend training mode was used to train the model, which simplified the processing flow of head pose estimation task. The experiments were completed on Pointing′04 and 300WLP datasets. The results show that the proposed model can effectively perform detection and estimation tasks on the premise of satisfying realtime requirements. The pitch prediction average absolute errors in the two datasets are respective 4.80 and 6.48 degrees, which fully proves the practicability and robustness of the proposed algorithm.
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