Back-Propagation Neural Network Based Face Detection and Pose Estimation


The KIPS Transactions:PartB , Vol. 9, No. 6, pp. 853-862, Dec. 2002
10.3745/KIPSTB.2002.9.6.853,   PDF Download:

Abstract

Face Detection can be defined as follows : Given a digitalized arbitrary image or image sequence, the goal of face detection is to determine whether or not there is any human face in the image, and if present, return its location, direction, size, and so on. This technique is based on many applications such face recognition, facial expression, head gesture and so on, and is one of important quality factors. But face in an given image is considerably difficult because facial expression, pose, facial size, light conditions and so on change the overall appearance of faces, thereby making it difficult to detect them rapidly and exactly. Therefore, this paper proposes fast and exact face detection which overcomes some restrictions by using neural network. The proposed system can be face detection irrelevant to facial expression, background and pose rapidly. For this, face detection is performed by neural network and detection response time is shortened by reducing search region and decreasing calculation time of neural network. Reduced search region is accomplished by using skin color segment and frame difference. And neural network calculation time is decreased by reducing input vector size of neural network. Principle Component Analysis (PCA) can reduce the dimension of data. Also, pose estimates in extracted facial image and eye region is located. This result enables to use more informations about face. The experiment measured success rate and process time using the Squared Mahalanobis distance. Both of still images and sequence images was experimented and in case of skin color segment, the result shows different success rate whether or not camera setting. Pose estimation experiments was carried out under same conditions and existence or nonexistence glasses shows different result in eye region detection. The experiment results show satisfactory detection rate and process time for real time system.


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Cite this article
[IEEE Style]
J. H. Lee, I. J. Jun, J. H. Lee, P. K. Rhee, "Back-Propagation Neural Network Based Face Detection and Pose Estimation," The KIPS Transactions:PartB , vol. 9, no. 6, pp. 853-862, 2002. DOI: 10.3745/KIPSTB.2002.9.6.853.

[ACM Style]
Jae Hoon Lee, In Ja Jun, Jung Hoon Lee, and Phill Kyu Rhee. 2002. Back-Propagation Neural Network Based Face Detection and Pose Estimation. The KIPS Transactions:PartB , 9, 6, (2002), 853-862. DOI: 10.3745/KIPSTB.2002.9.6.853.