Face Morphing
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Morphing involves transitioning between images by partitioning them into regions based on feature points like eyes and mouths. Face morphing algorithms find these points to warp and cross-dissolve images, transforming one face into another. Hollywood and Disney use face morphing for special effects and animation by speeding up transitions between character expressions or individuals. The process involves pre-processing, feature finding, image partitioning, coordinate transformations, and cross-dissolving regions to blend facial features between images.
Face Morphing
- 2. Morphing is tweening between different images. Morphing derives from “metamorphosis,” an ancient Greek word meaning “transformation.”
- 3. How’s Face Morphing done? Algorithms explains the extra feature of points on face and based on these feature points ,images are partitioned and morphing is performed Algorithms has been used to generate morphing between images of face of different people as well as between images of face of individuals
- 4. Dissolving (creates transition morphs) Warping (creates distortion morphs)
- 5. Where do we use face morphing? Hollywood film makers use novel morphing technologies to generate special effects Disney uses morphing to speed up the production of cartoons photoshop
- 6. Procedures Involved: Pre-Processing Feature Finding Eye-finding Mouth-finding Image Partitioning Coordinate Transformations Cross-Dissolving
- 7. Feature Finding Our goal was to find 4 major feature points, namely the two eyes, and the two end-points of the mouth. Within the scope of this project, we developed an eye- finding algorithm that successfully detect eyes at 84% rate.
- 8. Eye-finding We assume that the eyes are more complicated than other parts of the face we first compute the complexity map of the facial image by sliding a fixed-size frame and measuring the complexity within the frame in a "total variation" sense.
- 10. Image Partitioning: Our feature finder can give us the positions of the eyes and the ending points of the mouth, so we get 4 feature points Beside these facial features, the edges of the face also need to be carefully considered in the morphing algorithm totally we have 10 feature points for each face
- 11. • Based on these 10 feature points, our face-morpher partitions each photo into 16 non-overlapping triangular or quadrangular regions
- 12. • Cross-Dissolving • After performing coordinate transformations for each of the two facial figures, the feature points of these figures are matched. i.e., the left eye in one figure will be at the same position as the left eye in the other figure. • To complete face morphing, we need to do cross-dissolving as the coordinate transforms are taking place. Cross-dissolving is described by the following equation,
- 13. The following example demonstrates a typical morphing process original images of Ally and Lion
- 14. Cross-dissolve the two images to generate a new image. The new face possesses the features from both and the lion's Ally's faces
- 15. Morphing between faces of different cases Human and Animal (Lion)
- 16. Man And Man
- 17. Man and woman
- 18. Morphing between different images of the same person Happy <=== ===> Angry
- 19. Conclusion We believe that feature extraction is the key technique toward building entirely automatic face morphing algorithms we demonstrated that face morphing algorithm can help generate animation. Ideally speaking , the more feature points we can specify on the faces, the better morphing results we can obtain