Active Shape Model (ASM) MATLAB Toolbox for Face Recognition and Face Localization

This MATLAB toolbox implements the Active Shape Model (ASM) for face recognition and localization. ASM is a widely-used computer vision technique that employs statistical shape models trained on facial landmark datasets. The algorithm iteratively deforms an initial shape estimate to match new face images through gray-level profile matching and PCA-based shape constraints. Key functions include model training (build_shape_model), landmark initialization (initialize_search), and iterative fitting (fit_shape), which collectively enable automated face detection and alignment. In facial analysis applications, this toolbox supports facial expression recognition, face tracking, and pose estimation by maintaining temporal coherence in landmark positions. The implementation optimizes recognition accuracy through multi-resolution search strategies and improves efficiency with pre-computed texture models.

Recommendation: For researchers and developers working on face analysis, this ASM toolbox provides an accessible framework with modular functions for custom feature extraction and model extension. Its object-oriented design allows easy integration with MATLAB's Image Processing and Computer Vision toolboxes. The toolbox includes sample scripts for rapid prototyping, such as batch processing of face databases and real-time webcam integration. Whether for academic research or commercial applications, the toolbox's parameter tuning options and visualization utilities facilitate rapid development of robust face analysis systems. Download the toolbox to leverage its pre-trained models or retrain custom models using your own annotated datasets.