Using Dynamic Programming for Solving Variational Problems in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
A fast algorithm for active contours and curvature estimation
CVGIP: Image Understanding
A Bayesian Approach to Dynamic Contours Through Stochastic Sampling and Simulated Annealing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dynamic Programming for Detecting, Tracking, and Matching Deformable Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contour fitting using an adaptive spline model
BMVC '95 Proceedings of the 1995 British conference on Machine vision (Vol. 1)
Finite-Element Methods for Active Contour Models and Balloons for 2-D and 3-D Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Deformable Contours: Modeling and Extraction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Extending the Feature Vector for Automatic Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Robust Snake Implementation; A Dual Active Contour
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Human Face Detection in Cluttered Scenes
CAIP '95 Proceedings of the 6th International Conference on Computer Analysis of Images and Patterns
Multiple face contour detection based on geometric active contours
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Deformable pedal curves with application to face contour extraction
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Free boundary conditions active contours with applications for vision
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
Automatic extraction of face contours in images and videos
Future Generation Computer Systems
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Active contours are an attractive choice to extract the head boundary, for deployment within a face recognition or model-based coding scenario. However, conventional snake approaches can suffer difficulty in initialisation and parameterisation. A dual active contour configuration using dynamic programming has been developed to resolve these difficulties by using a global energy minimisation technique and a simplified parameterisation, to enable a global solution to be obtained. The merits of conventional gradient descent based snake (local) approaches, and search-based (global) approaches are discussed. In application to find head and face boundaries in front-view face images, the new technique employing dynamic programming is deployed to extract the inner face boundary, along with a conventional normal-driven contour to extract the outer (head) boundary. The extracted contours appear to offer sufficient discriminatory capability for inclusion within an automatic face recognition system.