Abstract
This article presents a real-time face detection and recognition system for mobile robots based on videos with a complex background. In the visual system, we propose a multi-information method consisting of an Adaboost algorithm, and color information for the face detection part. The interesting targets in the video will first be detected by the Adaboost algorithm, which is robust to illumination. Then the skin color model in YCbCr space will be employed to select the parts that may not be skin areas from the information detected by the Adaboost algorithm. An embedded hidden Markov model (EHMM) is presented, using a 2-DCT feature vector as the observation vector, to recognize the faces detected. The whole process of detecting and recognizing a frame, which is 320 × 240, will take 1.4 s with the rapid recognition parameters and 4.2 s with the slow recognition parameters.
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This work was presented in part and was awarded the Best Paper Award at the 15th International Symposium on Artificial Life and Robotics, Oita, Japan, February 4–6, 2010
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Chen, S., Zhang, T., Zhang, C. et al. A real-time face detection and recognition system for a mobile robot in a complex background. Artif Life Robotics 15, 439–443 (2010). https://doi.org/10.1007/s10015-010-0838-z
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DOI: https://doi.org/10.1007/s10015-010-0838-z