Myoung Ho Lee

A VOP generation tool: automatic segmentation of moving objects in image sequences based on spatio-temporal information

The new MPEG-4 video coding standard enables content-based functionalities. In order to support the philosophy of the MPEG-4 visual standard, each frame of video sequences should be represented in terms of video object planes (VOPs). In other words, video objects to be encoded in still pictures or video sequences should be prepared before the encoding process starts. Therefore, it requires a prior decomposition of sequences into VOPs so that each VOP represents a moving object. This paper addresses an image segmentation method for separating moving objects from the background in image sequences. The proposed method utilizes the following spatio-temporal information. (1) For localization of moving objects in the image sequence, two consecutive image frames in the temporal direction are examined and a hypothesis testing is performed by comparing two variance estimates from two consecutive difference images, which results in an F-test. (2) Spatial segmentation is performed to divide each image into semantic regions and to find precise object boundaries of the moving objects. The temporal segmentation yields a change detection mask that indicates moving areas (foreground) and nonmoving areas (background), and spatial segmentation produces spatial segmentation masks. A combination of the spatial and temporal segmentation masks produces VOPs faithfully. This paper presents various experimental results.

Geometry compression of 3-D mesh models using predictive two-stage quantization

In conventional predictive quantization schemes for 3-D mesh geometry, excessively large residuals or prediction errors, although occasional, lead to visually unacceptable geometric distortion. This is due to the fact that they cannot limit the maximum quantization error within a given bound. In order to completely eliminate the visually unacceptable distortion caused by large residuals, we propose a predictive two-stage quantization scheme. This scheme is very similar to the conventional DPCM, except that the embedded quantizer is replaced by a series of two quantizers. Each quantizer output is further compressed by an arithmetic code. When applied to typical 3-D mesh models, the scheme performs much better than the conventional predictive quantization methods and, depending upon the input models, even than the MPEG-4 compression method for 3-D mesh geometry both in rate distortion sense and in subjective viewing.

Development of an interactive contents authoring system for MPEG-4

The authoring system we present provides a powerful graphical user interface that helps a content creator produce MPEG-4 interactive contents easily and conveniently. In the presented authoring system, MPEG-4 content can be produced as two types of format such as a binary (MP4) and a textual format (XMT, extensible MPEG-4 textual). Especially, the presented authoring system manipulates arbitrarily shaped video objects and, also, provides a semi-automatic segmentation tool for extracting an arbitrarily shaped region of interest in a video object.

New block-matching algorithm for motion estimation based on predicted direction information

This paper proposes a new and efficient algorithm for block matching motion estimation. It reduces search times and improves performance of motion estimation. Instead of using the fixed first search point to be alike previous search algorithms to search motion vector, the proposed method finds more accurate first search point as to compensating search area using temporal correlation of motion vector. Therefore, the proposed method could reduce search times and improve the accuracy of motion estimation. The main idea of proposed method is based on the property of consistent directivity and center-biased distributions of motion vector. Simulation results show that the PSNR values are improved up to the 3.4 dB as depend on the image sequences and advanced about 1.5 dB on an average. The results of the comparison show that the performance of the proposed algorithm is better than those of other fast search algorithms whether the image sequence contains fast or slow motion, and is similar to the performance of the Full Search algorithm. Simulation results also show that the performance of the proposed scheme gives better subjective picture quality than the other fast search algorithms.