Abstract: A video object segmentation method is disclosed in the present invention. This video object segmentation method is for correctly segmenting video objects. In the video object segmentation method, the video objects to be firstly appeared in a video sequence are segmented in manual or semi-manual, and then the consecutive video frames is automatically segmented by an object-tracking based on the moving of the primarily segmented video object. In other words, the video object segmentation method applicable to a video system, comprises a first step of primarily segmenting objects existing in a frame of video sequence manually or semi-manually; and a second step of automatically segmenting the objects within the consecutive frames. This video object segmentation method can be adapted to a video system.

Abstract: The present invention provides the method of extracting temporal and spatial combination markers including the steps of: (1) simplifying inputted current image frames, quantizing the simplified images, and then extracting spatial markers from the simplified and quantized image frames using spatial information; (2) extracting temporal markers from inputted current image frames and previous image frames using temporal information, and (3) combining the extracted spatial marker and the extracted temporal marker to extract temporal and spatial markers.

Abstract: A video object segmentation method applicable to a video system is presented. The method includes primarily segmenting objects existing in a frame of a video sequence manually or semi-manually. The objects within a video sequence including the primarily segmented object are automatically segmented. The method also determines whether any scene change is made between consecutive frames or any new object other than the primarily segmented object appears within the video sequence being automatically segmented, when repeatedly performing automatically segmenting the objects within the video sequence for consecutive frames. And, the method repeatedly performs primarily segmenting objects existing in a frame of a video sequence manually or semi-manually if it is determined that any scene change is made between consecutive frames or any new object other than the primarily segmented object appears within the video sequence being automatically segmented.

Abstract: A video encoding apparatus includes a plurality of encoders for encoding each of a plurality of video programs received from external; a multiplexer for multiplexing outputs of the plurality of encoding means; a buffer for temporarily storing and transmitting signal multiplexed by the multiplexer; and a central controller for receiving monitoring information with respect to buffer fullness from the buffer and providing quantization parameters to be applied to respective pictures to be now encoded with the respective encoders. The sum of the bit rates of all the multiplexed video programs is constant, but each of the video programs allows for a variable bit rate (VBR) by synchronously controlling each of a video encoders by means of the central controller, thereby maintaining a relatively uniform picture quality within one picture.

Abstract: It is an object of the present invention to provide a method for automatically segmenting image objects by applying contour tracking to image objects with segmentation information of previous image object, and according to an aspect of the present invention, there is provided a method for segmenting an image object of a moving picture including the steps of: extracting and storing a contour of a previous image object of a previous scene by using a predetermined segmentation information of the previous image object; calculating a motion information by extracting a contour of the previous image object at a current scene; extracting a contour of a current image object by using the motion information and a space domain information of previous and current scenes; and extracting an image object area of the current image object at the current scene by using the contour of the current image object.

Abstract: A method of automatically dividing the domain of a motion picture is disclosed including the steps of: quantizing at least two sequential picture frames, and simplifying the shapes of the quantized picture frames; obtaining time space slope information from the quantized and simplified picture frames; detecting divides of the picture from the time space gradient information, and obtaining the boundaries between the divides, so as to divide the picture into multiple regions; combining neighboring smaller regions using graph theory, to thereby reduce the number of the divided regions; and dividing the regions into a motionless background object and moving objects, using motion information of the combined regions.

Abstract: A method for use in an object-oriented analysis-synthesis coder, for segmenting an image of a current frame into moving objects and describing each motion of the moving objects with a set of motion parameters, which comprises the steps of: (a) comparing the current frame with a preceding frame to detect a motion vector field; (b) sliding window blocks on the motion vector field, and computing the degree of homogeneity for each of the window blocks to produce a seed block; (c) determining a set of initial values for the set of motion parameters based on the seed block; (d) evaluating whether each motion vector contained in and around the seed block is describable with the set of initial values or not, to thereby detect a revised region; (e) determining a set of revised values for the set of motion parameters from the revised region; (f) evaluating whether each motion vector contained in and around the revised region is describable with the set of revised values or not, to thereby detect a newly revised region;

Abstract: A method, for use in an object-oriented analysis-synthesis coder, for segmenting an image signal into moving objects contained in a current frame and describing each motion of the moving objects with a set of motion parameters using a multi-stage segmentation comprises the steps of: (a) comparing the current frame with its preceding frame to detect a moving area in the current frame; (b) further comparing the current frame with the preceding frame to detect a motion vector for each pixel in the moving area, i.e., a motion vector field; (c) first segmenting the motion vector field by using a two dimensional translational patch model; (d) secondly segmenting the first stage segmenting results by using a planar patch model; and (e) thirdly segmenting the second-stage segmenting results by using a parabolic patch model.

Abstract: A processing block is processed by using an extension-interpolation ("E-I") method, wherein the processing block consisting of N.times.