Abstract: A data elementary buffer with underflow and overflow operational constraints is incorporated into a digital televison receiver to regulate the flow of data related to an ancillary data service to be presented in synchronization with a video or audio program element. The data elementary buffer ensures that data is received in time for decoding and presentation in synchronization with the video or audio element. The data elementary buffer also limits the amount of data that the receiver may be required to cache. The minimum size of the data elementary buffer is three times the size of a nominal data access unit or three times the quantity of data that the receiver can receive at the maximum rate in the period that a video element is displayed by the receiver.

Abstract: A method of determining a goodness metric of a module schedule. The module schedule comprises a plurality of modules, at least one of which exhibits multiple instances, that are arranged within the period of a carousel. The goodness metric is based, at least in part, upon the interval difference associated with each instance of all modules on the carousel. The interval difference for an instance of a module is the difference between the actual interval of the instance and a desired interval for that module.

Abstract: A carousel having multiple instances of at least one data or object module. The carousel may be encapsulated into a transmission, such as an MPEG-2 transport stream, for periodic transmission to a receiver.

Abstract: An apparatus for generating one or more carousels. A carousel includes a plurality of modules, at least one of which exhibits multiple instances, that are arranged in a module schedule. The apparatus may create, through multiple iterations, two or more module schedules for a carousel, and the optimum module schedule may then be selected and implemented on the carousel.

Abstract: An apparatus, computer readable medium, and method includes selecting and scheduling, substantially automatically, multimedia-content to be broadcast to a consumer, based on information obtained from at least one of the consumer and a storage area.

Abstract: A method of creating a module schedule for a carousel. The carousel includes a plurality of modules, at least one of which exhibits multiple instances within a period of the carousel. The method attempts to schedule each instance of a module at, or near, a desired interval of that module.

Abstract: An automatic segmentation system distinguishes foreground and background objects by first encoding and decoding a first image at a first time reference. Macroblocks are extracted from a second image at a second time reference. The macroblocks are mapped to pixel arrays in the decoded first image. Frame residuals are derived that represent the difference between the macroblocks and the corresponding pixel arrays in the previously decoded image. A global vector representing camera motion between the first and second images is applied to the macroblocks in the second image. The global vectors map the macroblocks to a second pixel array in the first decoded image. Global residuals between the macroblocks and the second mapped image arrays in the first image are derived. When the global residuals are compared with the frame residuals to determine which macroblocks are classified as background and foreground. The macroblocks classified as foreground are then blended into a mosaic.

Abstract: A mosaic image construction system includes at least one of a decoder receiving or an encoder transmitting a sequence of pixel data frames. The sequence includes at least a first pixel data frame and a second pixel data frame. The second pixel data frame is preferably temporally later than the first pixel data frame. The second pixel data frame has an associated parameter indicating the motion of the second frame with respect to the first frame and is used in the construction of the sequence of the pixel data frames. The mosaic image is constructed using at least the first and second pixel data frames together with the associated parameter.

Abstract: Automated summarization of digital video sequences is accomplished using a vector rank filter. The consecutive frames of a digital video sequence can be represented as feature vectors which are successively accumulated in a set of vectors. The distortion of the set by the addition of each successive vector or the cumulative distance from each successive vector to all other vectors in the set is determined by a vector rank filter. When the distortion exceeds a threshold value the end of a video segment is detected. Each frame in a video segment can be ranked according to its relative similarity to the other frames of the set by applying the vector rank filter to the feature vectors representing the video frames. To produce a summary of a video sequence which is most representative of the content of the sequence, frames are chosen that correspond to vectors that are the least distant to or produce the least distortion of the set of vectors representing the segment.

Abstract: A high-resolution image is derived from multiple low resolution images each having an array of low-resolution pixels. Motion vectors are derived at each of the unknown high-resolution grid points for each of the multiple low-resolution images. One motion vector is generated at each one of the high-resolution grid locations for each one of the multiple images. The motion vectors at the high-resolution grid points associate high-resolution grid points, whose values are unknown, with inter-pixel positions on the associated low-resolution images. Low-resolution pixels are identified that have the closest distance to each inter-pixel position. One or several of the identified low-resolution pixels having the shortest distance are used to determine the pixel value at each one of the high-resolution grid points. Pixel intensity values are then mapped into the high-resolution grid points according to the selected low-resolution pixels.

Abstract: A sprite-based coding system includes an encoder and decoder where sprite-building is automatic and segmentation of the sprite object is automatic and integrated into the sprite building as well as the coding process. The sprite object is distinguished from the rest of the video objects on basis of its motion. The sprite object moves according to the dominant component of the scene motion, which is usually due to camera motion or zoom. Hence, the sprite-based coding system utilizes dominant motion, to distinguish background images from foreground images. The sprite-based coding system is easily integrated into a video object-based coding framework such as MPEG-4, where shape and texture of individual video objects are coded separately.

Abstract: An automatic segmentation system distinguishes foreground and background objects by first encoding and decoding a first image at a first time reference. Macroblocks are extracted from a second image at a second time reference. The macroblocks are mapped to pixel arrays in the decoded first image. Frame residuals are derived that represent the difference between the macroblocks and the corresponding pixel arrays in the previously decoded image. A global vector representing camera motion between the first and second images is applied to the macroblocks in the second image. The global vectors map the macroblocks to a second pixel array in the first decoded image. Global residuals between the macroblocks and the second mapped image arrays in the first image are derived. When the global residuals are compared with the frame residuals to determine which macroblocks are classified as background and foreground. The macroblocks classified as foreground are then blended into a mosaic.

Abstract: A sprite-based coding system includes an encoder and decoder where sprite-building is automatic and segmentation of the sprite object is automatic and integrated into the sprite building as well as the coding process. The sprite object is distinguished from the rest of the video objects on basis of its motion. The sprite object moves according to the dominant component of the scene motion, which is usually due to camera motion or zoom. Hence, the sprite-based coding system utilizes dominant motion, to distinguish background images from foreground images. The sprite-based coding system is easily integrated into a video object-based coding framework such as MPEG-4, where shape and texture of individual video objects are coded separately. The automatic segmentation integrated in the sprite-based coding system identifies the shape and texture of the sprite object.

Abstract: An adaptive spatio-temporal compression/decompression algorithm for a video image uses a quadtree hierarchy to represent each frame of the image, the quadtree hierarchy including intermediary nodes and leaves. For each leaf a temporal bit is added indicative of whether a significant intensity change occurred between two frames of the video image. If the temporal bit indicates the significant intensity change occurred between frames, then a new intensity value also is added to that leaf. A decoder using a state machine extracts from the resulting compressed data stream a start address, a block size and the new intensity value for each leaf having the significant intensity change between frames to update a display memory with the new intensity value at each pixel within the area defined by the start address and block size.

Abstract: A two-dimensional array of binary values is used to control operation of a bi-level imaging device. The array of binary values is formed by applying an enhanced array g(u,v) to a two-dimensional array of threshold values. A two-dimensional array of pixel value f(u,v) is used to form the enhanced array g(u,v) such that g(u,v)=m.sub.f +k[f(u,v)-m.sub.f ] where m.sub.f is the average value of f(u+a, v+b) from a=-L to a=+L and b=-M to b=+M and k is a gain function which depends on the standard deviation in f(u+c, v+d) from c=-N to c=+N and d=-P to d=+P. L, M, N and P define the sub-array over which the standard deviation is calculated. Preferably, L, M, N and P are each equal to 2. The value of k is a decreasing function of the standard deviation: the larger the standard deviation, the smaller the gain factor k. The rate at which k decreases with increase in the standard deviation depends on the edge sampling characteristics of the array of threshold values.