Edge-based effective active appearance model for real-time wrinkle detection.

Background: Recently, the field of face and facial features has been progressively studied. The features of facial expression have gained increasing attention for related applications. The wrinkle is the most representative feature, and its research and applications have been topics of high interest. Wrinkles play an important role in face feature analysis. They have been widely used in applications, such as age estimation, skin texture classification, expression recognition, and simulation.

Purpose: Existing approaches to the image-based analysis of wrinkles as texture not as curvilinear discontinuity and wrinkle detection mainly have focused on detecting wrinkles on forehead position, which is usually horizontal linear shapes, while the detection of the nasolabial wrinkle is not well understood due to their variety of shapes and complexity.

Method: In this paper, we present a nasolabial wrinkle line detecting effective algorithm based on the Active appearance model and Hessian filter to improve localization results by creating unique initial shapes of the wrinkle lines for each input face image.

Results: Experimental results show that the proposed method is capable of tracking curve wrinkle lines, thus allowing to detect complexly structured wrinkle lines. This work demonstrates results illustrated the competitiveness of the proposed method in detecting nasolabial wrinkle lines.

Conclusion: In our study, this was introduced the effectiveness of changing the structure of AAM and successfully applied in wrinkle line localizing, although competitive results are achieved by the proposed wrinkle detection method.