Showing papers by "Michael G. Strintzis published in 1999"

Tracking the left ventricle in echocardiographic images by learning heart dynamics

Abstract: In this paper a temporal learning-filtering procedure is applied to refine the left ventricle (LV) boundary detected by an active-contour model. Instead of making prior assumptions about the LV shape or its motion, this information is incrementally gathered directly from the images and is exploited to achieve more coherent segmentation. A Hough transform technique is used to find an initial approximation of the object boundary at the first frame of the sequence. Then, an active-contour model is used in a coarse-to-fine framework, for the estimation of a noisy LV boundary. The PCA transform is applied to form a reduced ordered orthonormal basis of the LV deformations based on a sequence of noisy boundary observations. Then this basis Is used to constrain the motion of the active contour in subsequent frames, and thus provide more coherent identification. Results of epicardial boundary identification in B-mode images are presented.

Object-based coding of stereoscopic and 3D image sequences

Abstract: The author begins by discussing what object based coding is and goes on to consider the structure of object based stereoscopic coders. Different techniques for object-based stereoscopic image sequence coding are reviewed. These techniques basically differ in the way they define models and estimate model parameters. We review the various models used for representing motion and structure. Then we review segmentation techniques, and discuss coding of object parameters and image synthesis.

3D object articulation and motion estimation in model-based stereoscopic videoconference image sequence analysis and coding

Abstract: This paper describes a procedure for model-based analysis and coding of both left and right channels of a stereoscopic image sequence The proposed scheme starts with a hierarchical dynamic programming technique for matching across the epipolar line for efficient disparity/depth estimation Foreground/background segmentation is initially based on depth estimation and is improved using motion and luminance information The model is initialised by the adaptation of a wireframe model to the consistent depth information Robust classification techniques are then used to obtain an articulated description of the foreground of the scene (head, neck, shoulders) The object articulation procedure is based on a novel scheme for the segmentation of the rigid 3D motion fields of the triangle patches of the 3D model object Spatial neighbourhood constraints are used to improve the reliability of the original triangle motion estimation The motion estimation and motion field segmentation procedures are repeated iteratively until a satisfactory object articulation emerges The rigid 3D motion is then re-computed for each sub-object and finally, a novel technique is used to estimate flexible motion of the nodes of the wireframe from the rigid 3D motion vectors computed for the wireframe triangles containing each specific node The performance of the resulting analysis and compression method is evaluated experimentally

Sprite generation and coding of multiview image sequences

Abstract: An algorithm to generate background sprite images from multiview image sequences is presented. A dynamic programming algorithm, using a multiview matching cost as well as pure geometrical constraints, is used to provide an estimate of the disparity field and to identify occluded areas. By combining motion, disparity and occlusion information, a sprite image corresponding to the first (main) view at the first time instant is generated. Image pixels from other views that are occluded in the main view are added to the sprite. The sprite coding method defined by MPEG-4 is extended for multiview image sequences, based on the generated sprite. Experimental results are presented, demonstrating the performance of the proposed technique and comparing it with methods using sprite generation from monoscopic sequences.

Multiview sprite generation and coding

Abstract: An algorithm to generate background sprite images from multiview image sequences is presented. A dynamic-programming algorithm, first proposed in Grammalidis and Strinzis (1998), using a multiview matching cost as well as pure geometrical constraints, is used to provide an estimate of the disparity field and to identify occluded areas. By combining motion, disparity and occlusion information a sprite image corresponding to the first (main) view at the first time instant is generated. Image pixels from other views that are occluded in the main view are also added to the sprite. The sprite coding method defined by MPEG-4 is extended for multiview image sequences, based on the generated sprite. Experimental results demonstrating the performance of the proposed technique and comparing it with methods using sprite generation from monoscopic sequences are presented.

Three Dimensional Model Adaptation and Tracking of a Human Face

Abstract: This paper develops a methodology consisting of improved previously known methods and novel techniques for the model based coding of a human face. An image scene is analysed to locate the position of human faces and transform a generic three dimensional face model to reflect the characteristics extracted from the particular image. A set of feature points necessary to define the position and posture of the face is tracked through the image sequence and the three dimensional model is continuously adapted to the facial image of every subsequent frame. Results are shown for every individual module, while on going work aims to the integration of the component modules.

Object Articulation Based on Local 3D Motion Estimation

Abstract: This paper describes a 3D model-based unsupervised procedure for the segmentation of multiview image sequences using multiple sources of information. Using multiview information a 3D model representation of the scene is constructed. The articulation procedure is based on the homogeneity of parameters, such as rigid 3D motion, color and depth, estimated for each sub-object, which consists of a number of interconnected triangles of the 3D model. The rigid 3D motion of each sub-object for subsequent frames is estimated using a Kalman filtering algorithm taking into account the temporal correlation between consecutive frames. Information from all cameras is combined during the formation of the equations for the rigid 3D motion parameters. The parameter estimation for each sub-object and the 3D model segmentation procedures are interleaved and repeated iteratively until a satisfactory object segmentation emerges. The performance of the resulting segmentation method is evaluated experimentally.

Digital Signal Processing for the Analysis and Coding of Stereoscopic and 3D Video

Abstract: The main problem in stereo vision is the reconstruction of the 3D surface of objects in the scene from a pair of stereo images. This is performed by establishing correspondence between homologous points in each stereo image. Once correspondence is established it is straightforward to compute the coordinates of the corresponding 3D point. Although, important image analysis tasks like scene segmentation and 3D motion estimation may be performed using a monocular sequence, one may achieve better result by exploiting depth information from a stereo image sequence. Especially if depth estimation is combined with 3D motion estimation a considerable improvement in the accuracy of the estimates is expected. In this paper we present algorithms for the analysis of stereoscopic image sequences. Apart from the usefulness of stereoscopic imagin in compute revision, its application in advanced telecommunications is also of prime importance. Since the bandwidth required to transmit both stereoscopic image streams is large, efficient coding technique should be employed to reduce the data rate. In this paper we present an object-based approach that lacks the disadvantages of tradition block-based techniques. Also, the ability of this algorithm to describe a scene in a structural way, in contrast to traditional waveform-based coding techniques, opens new areas of applications.