How Do I Morph Two Pictures Together?

Image deformation is a common method in image processing. It refers to changing one image into another according to certain rules or methods. Image deformation has a wide range of applications in practical fields. For example, in satellite image and ultrasound image processing, it is used to correct image distortion caused by the inherent limitations of tools or methods. In medical image processing and 3D reconstruction, deformation is used In positioning, matching and other technologies, in image editing and artistic design, some special effects can be achieved by using deformation.

As an application of computer vision, the problem of image deformation has received much attention in recent years, and its value is constantly being improved and developed in research and practice. We apply image warping techniques to generate smooth transitions from one digital image to another, or to produce amazing visual effects based on transformations between multiple images. Image warping technology has a wide range of applications.

Pioneer of image distortion,

Image deformation methods can be widely used in science fiction movie production, 3D reconstruction, criminal detection, surgical face plastic surgery effect prediction, face detection and face image synthesis. Image distortion was initially associated with the visual effects of the entertainment industry. The forced, smooth transition of vision was created by a comprehensive intermediate image between the provided image pairs. These deformation results should be attributed to the geometry maintained throughout the entire image sequence. queue.

In medical imaging, CT and MRI scans can be obtained on a fixed slice resolution line. Although the middle slice can be calculated by the traditional linear, cubic or more order interpolation function, this traditional method does not consider the basic structural structure of the tissue being imaged. Better results can be obtained by establishing a correspondence of features between successive pairs of scans, which can include tissue crossing boundaries and physiological landmarks. The calculated deformed images constitute intermediate images, which conform to the geometric correspondence provided by the user. Ruprecht and Muller describe work in this area. Automatic feature selection is still an active research area, as most of the feature selection work is currently done manually.

The latest face recognition research work also uses deformation techniques. Bichsel proposed a new method for generating optimal mappings when changing from one graph to another. This mapping can be calculated by maximizing the probability of the deformation field in a Bayesian frame. This method uses a recursive approximation: near the current deformation field, the probability distribution is approximately calculated from the Gaussian probability distribution. For this Gaussian probability distribution, the most likely solution is estimated by linear algebra techniques. This method has been used to perform interpolation between different visions of the same face and between different face images. This technique has been proven in the application of face recognition under different visual and lighting conditions. Covell proposed an automatic image deformation method to restore facial features. At the same time, Bregler proved that this technology can be used to synchronize lips. Wolberg once proposed using video rewriting to automatically synthesize human faces. Animation system, which can be used for dubbing movies, teleconferencing and special effects.

In the work on face analysis and synthesis, Ezzat and Poggio used an image-based face modeling method. In this method, they used instance images to model facial movements. They used visual field interpolation for image synthesis. The feasibility of the method, a learning network is aligned on the example images, and each image is associated with a position in a high-level, multidimensional parameter space representing poses and expressions to estimate pose, eye, and mouth movements and head translation , Rotation, and scaling, Wolberg confirmed his busy synthetic analysis techniques.

In short, with the development of image deformation technology, it will certainly be applied to more fields.