Search Word(s) in Title, Keywords, Authors, and Abstract: Active Appearance Model

Feasibility Study of a Distributed and Parallel Environment for Implementing the Standard Version of AAM Model
Moulkheir Naoui, Saïd Mahmoudi and Ghalem Belalem
Page: 149~168, Vol. 12, No.1, 2016
10.3745/JIPS.02.0039

Keywords: Active Appearance Model, Data Parallelism, Deformable Model, Distributed Image Processing, Parallel Image Processing, Segmentation
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The Active Appearance Model (AAM) is a class of deformable models, which, in the segmentation process, integrates the priori knowledge on the shape and the texture and deformation of the structures studied. This model in its sequential form is computationally intensive and operates on large data sets. This paper presents another framework to implement the standard version of the AAM model. We suggest a distributed and parallel approach justified by the characteristics of the model and their potentialities. We introduce a schema for the representation of the overall model and we study of operations that can be parallelized. This approach is intended to exploit the benefits build in the area of advanced image processing.


Age Invariant Face Recognition Based on DCT Feature Extraction and Kernel Fisher Analysis
Leila Boussaad, Mohamed Benmohammed and Redha Benzid
Page: 392~409, Vol. 12, No.3, 2016
10.3745/JIPS.02.0043

Keywords: Active Appearance Model, Age-Invariant, Face Recognition, Kernel Fisher Analysis, 2D-Discrete Cosine Transform
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The aim of this paper is to examine the effectiveness of combining three popular tools used in pattern recognition, which are the Active Appearance Model (AAM), the two-dimensional discrete cosine transform (2D-DCT), and Kernel Fisher Analysis (KFA), for face recognition across age variations. For this purpose, we first used AAM to generate an AAM-based face representation; then, we applied 2D-DCT to get the descriptor of the image; and finally, we used a multiclass KFA for dimension reduction. Classification was made through a K-nearest neighbor classifier, based on Euclidean distance. Our experimental results on face images, which were obtained from the publicly available FG-NET face database, showed that the proposed descriptor worked satisfactorily for both face identification and verification across age progression.


Recognition of Human Facial Expression in a Video Image using the Active Appearance Model
Gyeong-Sic Jo and Yong-Guk Kim
Page: 261~268, Vol. 6, No.2, 2010
10.3745/JIPS.2010.6.2.261
Keywords: Active Appearance Model, Facial Expression Recognition, Image Alignment Method
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Tracking human facial expression within a video image has many useful applications, such as surveillance and teleconferencing, etc. Initially, the Active Appearance Model (AAM) was proposed for facial recognition; however, it turns out that the AAM has many advantages as regards continuous facial expression recognition. We have implemented a continuous facial expression recognition system using the AAM. In this study, we adopt an independent AAM using the Inverse Compositional Image Alignment method. The system was evaluated using the standard Cohn-Kanade facial expression database, the results of which show that it could have numerous potential applications.