A multimedia coding standard, MPEG4 has frozen its Committee Draft (CD) as the MPEG4 version 1 CD, last October. It defines Audio-Visual (AV) coding Algorithms and their System Multiplex/Composition formats. Founding on Object-base concept, Video part adopts Shape Coding technology in addition to conventional Texture Coding skills. Audio part consists of voice coding tools (HVXC and CELP core) and audio coding tools (HILN and MPEG2 AAC or Twin VQ). Error resilience technologies and Synthetic and Natural Hybrid Coding (SNHC) technologies are the MPEG4 specific features. System part defines flexible Multiplexing of audio-visual bitstreams and Scene Composition for user-interactive re-construction of the scenes at decoder side. The version 1 standardization will be finalized in 1998, with some possible minute changes. The expected application areas are real-time communication, mobile multimedia, internet/intranet accessing, broadcasting, storage media, surveillance, and so on.

Video compression technologies such as MPEG have enabled the efficient use of video data in the computer environment. However, the compressed video information still has a huge amount of data compared with the other media such as text, audio, and graphics. Therefore, it is very important to handle the video information in a networked database for the efficient use of resources like storage media. Furthermore, in the networked database, its retrieval methods including search and delivery become the key issues especially for the video information which requires a large network bandwidth. In this paper, a video browsing method using an automatic fast scene cut detection for networked video database access is described. The scene cut is defined as the scene change frame and is detected by temporal change in interframe luminance difference and chrominance correlation which are obtained from spatio-temporally scaled image directly extracted from the MPEG compressed video without any complex processing of video decoding. The detected scene change frames are further investigated to exploit the relationship between the scene cuts and are classified in order to make a hierarchical indexing. These results of detection are stored as an scene index file using the MPEG format. The simulation results are also presented for several test video sequences to show that these methods have enabled the efficient video database construction and accessing.

We can understand and recover a scene even from a picture or a line drawing. A number of methods have been developed for solving this problem. They have scarcely aimed to deal with scenes of multiple objects although they have ability to recognize three-dimensional shapes of every object. In this paper, challenging to solve this problem, we describe a method for deciding configurations of multiple objects. This method employs the assumption of coplanarity and the constraint of occlusion. The assumption of coplanarity generates the candidates of configurations of multiple objects and the constraint of occlusion prunes impossible configurations. By combining this method with a method of shape recovery for individual objects, we have implemented a system acquirig a three-dimensional information of scene including multiple objects from a monocular image.

High variability of object features and bad class separation of objects are the main causes for the difficulties encountered during the interpretation of ground-level natural scenes. For coping with these two problems we propose a method which extracts those regions that can be segmented and immediately recognized with sufficient reliability (core regions) in the first stage, and later try to extend these core regions up to their real object boundaries. The extraction of reliable core regions is generally difficult to achieve. Instead of using fixed sets of features and fixed parameter settings, our method employs multiple local features (including textural features) and multiple parameter settings. Not all available features may yield useful core regions, but those core regions that are extracted from these multiple features make a cntributio to the reliability of the objects they represent. The extraction mechanism computes multiple segmentations of the same object from these multiple features and parameter settings, because it is not possible to extract such regions uniquely. Then those regions are extracted which satisfy the constraints given by knowledge about the objects (shape, location, orientation, spatial relationships). Several spatially overlapping regions are combined. Combined regions obtained for several features are integrated to form core regions for the given object calss.

We describe an approach to describe moving pictures in terms of their structural properties for video editing, video indexing, and video coding. The description contains 2D shape, motion, spatial relation, and relative depth of each region. To obtain the description, we develop the incremental segmentation scheme which includes dynamic occlusion analysis to determine relative depths of several objects. The scheme has been designed along the analysis-by-synthesis" approach, and uses a sequence of images to estimate object boundaries and motion information successively/incrementally. The scheme consists of three components: motion estimation, prediction with dynamic occlusion analysis, and update of the segmentation results. By combining the information from extended (longer) image sequences, and also by treating the segmentation and dynamic occlusion analysis simultaneously, the scheme attempts to improve successively over time the accuracy of the object boundary and motion estimation.

This paper describes a method for describing a three-dimensional (3-D) scene by integrating color and range data. Range data is obtained by a feature-based stereo method developed in our laboratory. A color image is segmented into uniform color regions. A plane is fitted to the range data inside a segmented region. Regions are classified into three types based on the range data. A certain types of regions are merged and the others remain unless the region type is modified. The region type is modified if the range data on a plane are selected by removing of the some range data. As a result, the scene is represented by planar surfaces with homogeneous colors. Experimental results for real scenes are shown.