Abstract:
An encoder/decoder uses “self-referencing” frames. For example, a second B-field in a current frame references the first B-field from the current frame in motion compensated prediction. Allowing the first B-field in a frame to act as a reference for the second B-field in the frame allows more accurate prediction of the second B-field, while also preserving the temporal scalability benefits of having B-fields in the current frame.
Abstract:
In one aspect, for a first interlaced video frame in a video sequence, a decoder decodes a bitplane signaled at frame layer for the first interlaced video frame. The bitplane represents field/frame transform types for plural macroblocks of the first interlaced video frame. For a second interlaced video frame in the video sequence, for each of at least one but not all of plural macroblocks of the second interlaced video frame, the decoder processes a per macroblock field/frame transform type bit signaled at macroblock layer. An encoder performs corresponding encoding.
Abstract:
For interlaced B-frames, an encoder/decoder computes direct mode motion vectors for a current macroblock by selecting at most one representative motion vector for each of the top and bottom fields of the co-located macroblock of the previously decoded, temporally subsequent anchor. For example, the selecting is performed based at least in part on the mode of coding the current interlaced B-frame's macroblock (e.g., 1MV mode, 2 Field MV mode, etc.). For interlaced B-fields, an encoder/decoder selects direct mode motion vectors using logic that favors the dominant polarity if the corresponding macroblock in the corresponding field of the next anchor picture was coded using four motion vectors. For example, if the corresponding macroblock's same polarity motion vectors outnumber its opposite polarity motion vectors, the encoder/decoder calculates the median of the same polarity motion vectors to obtain a motion vector for deriving direct mode motion vectors.
Abstract:
An encoder/decoder switches prediction modes between the fields in a field-coded macroblock of an interlaced B-frame. For example, the encoder/decoder switches between a forward prediction mode for the top field and a backward mode for the bottom field in the field-coded macroblock. Switching between forward and backward prediction modes within the same field-coded macroblock allows more flexibility to find efficient prediction modes for different portions of interlaced B-frames.
Abstract:
The present invention extends to methods, systems, and computer program products for deriving document similarity indices. Embodiments of the invention include scalable and efficient mechanisms for deriving and updating a document similarity index for a plurality of documents. The number of maintained similarities can be controlled to conserve CPU and storage resources.
Abstract:
The present invention extends to methods, systems, and computer program products for identifying key phrases within documents. Embodiments of the invention include using a tag index to determine what a document primarily relates to. For example, an integrated data flow and extract-transform-load pipeline, crawls, parses and word breaks large corpuses of documents in database tables. Documents can be broken into tuples. The tuples can be sent to a heuristically based algorithm that uses statistical language models and weight+cross-entropy threshold functions to summarize the document into its “top N” most statistically significant phrases. Accordingly, embodiments of the invention scale efficiently (e.g., linearly) and (potentially large numbers of) documents can be characterized by salient and relevant key phrases (tags).
Abstract:
For interlaced B-fields or interlaced B-frames, forward motion vectors are predicted by an encoder/decoder using forward motion vectors from a forward motion vector buffer, and backward motion vectors are predicted using backward motion vectors from a backward motion vector buffer. The resulting motion vectors are added to the corresponding buffer. Holes in motion vector buffers can be filled in with estimated motion vector values. An encoder/decoder switches prediction modes between fields in a field-coded macroblock of an interlaced B-frame. For interlaced B-frames and interlaced B-fields, an encoder/decoder computes direct mode motion vectors. For interlaced B-fields or interlaced B-frames, an encoder/decoder uses 4 MV coding. An encoder/decoder uses “self-referencing” B-frames. An encoder sends binary information indicating whether a prediction mode is forward or not-forward for one or more macroblocks in an interlaced B-field. An encoder/decoder uses intra-coded B-fields [“BI-fields”].
Abstract:
Forward motion vectors are predicted by an encoder/decoder using previously reconstructed (or estimated) forward motion vectors from a forward motion vector buffer, and backward motion vectors are predicted using previously reconstructed (or estimated) backward motion vectors from a backward motion vector buffer. The resulting motion vectors are added to the corresponding buffer. Holes in motion vector buffers can be filled in with estimated motion vector values. For example, for interlaced B-fields, to choose between different polarity motion vectors (e.g., “same polarity” or “opposite polarity”) for hole-filling, an encoder/decoder selects a dominant polarity field motion vector. The distance between anchors and current frames is computed using various syntax elements, and the computed distance is used for scaling reference field motion vectors.
Abstract:
An encoder/decoder uses “self-referencing” frames. For example, a second B-field in a current frame references the first B-field from the current frame in motion compensated prediction. Allowing the first B-field in a frame to act as a reference for the second B-field in the frame allows more accurate prediction of the second B-field, while also preserving the temporal scalability benefits of having B-fields in the current frame.
Abstract:
The described implementations relate to speech interfaces and in some instances to speech pattern recognition techniques that enable speech interfaces. One system includes a feature pipeline configured to produce speech feature vectors from input speech. This system also includes a classifier pipeline configured to classify individual speech feature vectors utilizing multi-level classification.