We describe a novel approach for matching and recognition , based on deformable intensity surfaces. In this approach, the intensity surface of the image is modeled as a deformable thin plate, and its strain energy while deforming to a new image is measured for recognition. Each surface point has 3 degrees of freedom, thus capturing ne surface changes. The method is validated for recognition and...

We present a model-based approach to recover the rigid and non-rigid facial motion parameters in video sequences. Our face model is based on anatomically motivated muscle actuator controls to model the articulated non-rigid motion of a human face. The model is capable of generating a variety of facial expressions by using a small number of muscle actuator controls. We estimate rigid and non-rig...

We describe a novel technique for face recognition based on deformable intensity surfaces which incorporates both the shape and texture components of the 2D image. The intensity surface of the facial image is modeled as a deformable 3D mesh in (x;y; I(x;y)) space. Using an e cient technique for matching two surfaces (in terms of the analytic modes of vibration), we obtain a dense correspondence...

Deformable model tracking is a powerful methodology that allows us to track the evolution of high-dimensional parameter vectors from uncalibrated monocular video sequences. The core of the approach consists of using low-level vision algorithms, such as edge trackers or optical flow, to collect a large number of 2D displacements, or motion measurements, at selected model points and mapping them ...

We present a model-based approach to recover the rigid and non-rigid facial motion parameters in video sequences. Our face model is based on anatomically motivated muscle actuator controls to model the articulated non-rigid motion of a human face. The model is capable of generating a variety of facial expressions by using a small number of muscle actuator controls. We estimate rigid and non-rig...

This paper presents an integrated system for face detection and tracking in video sequences. The system consists of two modules, namely face detection and face tracking. The automatic face detection is based on a non-holistic object detection approach that utilizes the appearance and the topology of facial components to robustly detect faces in images. Both statistical and structural pattern re...

This paper tackles the problem of accurately matching a 3D deformable face model to images in challenging real-world scenarios with large amounts of head movement, occlusion, and difficult lighting conditions (Figure 2). A baseline system [1] based on the ASM [2] involves searching with a set of view-dependent local patches to locate image features and using their positions to update the face s...

assessment of cardiac right‑ventricle functions plays an essential role in diagnosis of arrhythmogenic right ventricular dysplasia (arvd). among clinical tests, cardiac magnetic resonance imaging (mri) is now becoming the most valid imaging technique to diagnose arvd. fatty infiltration of the right ventricular free wall can be visible on cardiac mri. finding right‑ventricle functional paramete...

We present a method for estimating the shape of a deformable model using the least-squares residuals from a model-based optical flow computation. This method is built on top of an estimation framework using optical flow and image features, where optical flow affects only the motion parameters of the model. Using the results of this computation, our new method adjusts all of the parameters so th...