Paper Info
Title
A unified approach for combining ASM into AAM
Abstract
Since the goal of Active Appearance Model (AAM) is to minimize the residual error between the model appearance and the input image, it often fails to converge accurately to the landmark points of the input image. To alleviate this weakness, we have combined Active Shape Model (ASM) into AAM, where ASM tries to find correct landmark points using the local profile model. Because the original objective function and search scheme of the ASM is not appropriate for combining these methods, we modified the objective function of the ASM and proposed a new objective function that combining that of two methods. The proposed objective function can be optimized using a gradient based algorithm as in the AAM. Experimental results show that the proposed method reduces the average fitting error when compared with existing fitting methods such as ASM, AAM, and Texture Constrained-ASM (TC-ASM).
Year
DOI
Venue
2006
10.1007/11949534_35
PSIVT
Keywords
Field
DocType
unified approach,active appearance model,original objective function,proposed objective function,new objective function,active shape model,correct landmark point,input image,objective function,average fitting error
Active shape model,Residual,Computer vision,Search algorithm,Pattern recognition,Computer science,Image processing,Image segmentation,Active appearance model,Artificial intelligence,Landmark,Abstract machine
Conference
Volume
ISSN
ISBN
4319
0302-9743
3-540-68297-X
Citations 
PageRank 
References 
0
0.34
9
Authors
2
Name
Order
Citations
PageRank
Jaewon Sung11529.57
Daijin Kim21882126.85