Dolby Laboratories Licensing Corporation

Claus Bauer

Regunathan Radhakrishnan

Wenyu Jiang

Lie Lu

Brett Graham Crockett

Charles Quito Robinson

Mingqing Hu

Ming Wang

Rhonda J Wilson

Hyung-Suk Kim

Brian David Link

Kent Bennett Terry

Poppy Crum

Tianshi Gao

Eric Gsell

Glenn N Dickins

Jeffrey Charles Riedmiller

Mark Stuart Vinton

Grant Allen Davidson

Matthew Conrad Fellers

Corey I Cheng

Junfeng He

Regunthan Radhakrishnan

Example embodiments disclosed herein relate to perception based multimedia processing. There is provided a method for processing multimedia data, the method includes automatically determining user perception on a segment of the multimedia data based on a plurality of clusters, the plurality of clusters obtained in association with predefined user perceptions and processing the segment of the multimedia data at least in part based on determined user perception on the segment. Corresponding system and computer program products are disclosed as well.

Perception based multimedia processing

Attributes are identified in media content. A classification value of the media content is computed based on the identified attributes. Thereafter, a fingerprint derived from the media content is stored or searched for based on the classification value of the media content.

Storing and searching fingerprints derived from media content based on a classification of the media content

Techniques for re-associating dynamic metadata with media data are provided. A media processing system creates, with a first media processing stage, binding information comprising dynamic metadata and a time relationship between the dynamic metadata and media data. The binding information may be derived from the media data. While the first media processing stage delivers the media data to a second media processing stage in a first data path, the first media processing stage passes the binding information to the second media processing stage in a second data path. The media processing system re-associates, with the second media processing stage, the dynamic metadata and the media data using the binding information.

Alignment and re-association of metadata for media streams within a computing device

Methods, apparatuses and program logic in storage media to process media data for quality enhancement. The media data is for rendering at a wireless device. Environmental quantities are accepted from one or more sensors located remote from the wireless device but sufficiently close to be indicative of similar quantities in the device's environment. The sensors at in or connected to a network node. At the network node, the method includes processing the media data using the environmental quantities to generate processed data, and wirelessly sending the processed output to the resource constrained device for rendering, such that the processed output is usable by the resource constrained device to render or to process and render the media data.

Upstream signal processing for client devices in a small-cell wireless network

Methods, apparatuses and program logic in non-transitory media to process video data for quality enhancement. Information is accepted from a resource constrained device, e.g., a wireless portable device related to the quality enhancement and/or environmental quantities such as ambient lighting for the device. The video data is processed to achieve quality enhancement using at least some of the accepted information to generate processed output. The processing of the video data includes processing when or where one or more resources sufficient for the processing are available.

Upstream quality enhancement signal processing for resource constrained client devices

Embodiments of identifying multimedia objects based on multimedia fingerprints are provided. Query fingerprints are derived from a multimedia object according to differing fingerprint algorithms. For each fingerprint algorithm, decisions are calculated through at least one classifier corresponding to the fingerprint algorithm based on the query fingerprint and reference fingerprints, the reference fingerprints being derived from reference multimedia objects according to the same fingerprint algorithm. Each of the decisions indicates a possibility that the query fingerprint and the reference fingerprint are not derived from the same multimedia content. For each of the reference multimedia objects, a distance is calculated as a weighted sum of the decisions relating to the reference fingerprints. The multimedia object is identified as matching the reference multimedia object with the smallest distance less than a threshold.

Identifying multimedia objects based on multimedia fingerprint

A portion of media content is accessed. Components from a first and each subsequent spatial regions of the media content are sampled. Each spatial region has an unsegmented area. Each subsequent spatial region includes those within its area as elements thereof or the spatial regions may partially overlap. The regions may overlap independent of a hierarchical relationship between the regions. A media fingerprint is derived from the components of each of the spatial regions, which reliably corresponds to the media content portion, e.g., over geometric attacks such as rotation.

Media fingerprints that reliably correspond to media content with projection of moment invariants

Techniques are provided for dynamic configuration of search parameters for multimedia fingerprint databases that use weak bits. A multimedia fingerprint database, which stores reference fingerprints and uses weak bits, is maintained. Maintaining the database includes dynamically configuring one or more of the following parameters: a fingerprint length of those portions of the reference fingerprints that are used to identify multimedia objects; an index length of the index used to index those portions of the reference fingerprints that are used to identify multimedia objects; a threshold that is used to determine whether multimedia objects are correctly identified; and a number of the weak bits in the reference fingerprints.

Method to dynamically design and configure multimedia fingerprint databases

Methods, apparatuses and program logic in storage media to process media data for quality enhancement. Information is accepted from a resource constrained device, e.g., a wireless portable device related to the quality enhancement and/or environmental quantities such as background noise and/or ambient lighting for the device. Media data is data processed to achieve quality enhancement using at least some of the accepted information to generate processed output. The data processing of the media data includes processing when or where one or more resources sufficient for the processing are available.

Robust media fingerprints are derived from a portion of audio content. A portion of content in an audio signal is categorized. The audio content is characterized based, at least in part, on one or more of its features. The features may include a component that relates to one of several sound categories, e.g., speech and/or noise, which may be mixed with the audio signal. Upon categorizing the audio content as free of the speech or noise related components, the audio signal component is processed. Upon categorizing the audio content as including the speech related component and/or the noise related components, the speech or noise related components are separated from the audio signal. The audio signal is processed independent of the speech related component and/or the noise related component. Processing the audio signal includes computing the audio fingerprint, which reliably corresponds to the audio signal.

Robust media fingerprints

Signatures that can be used to identify video and audio content are generated from the content by generating measures of dissimilarity between features of corresponding groups of pixels in frames of video content and by generating low-resolution time-frequency representations of audio segments. The signatures are generated by applying a hash function to intermediate values derived from the measures of dissimilarity and to the low-resolution time-frequency representations. The generated signatures may be used in a variety of applications such as restoring synchronization between video and audio content streams and identifying copies of original video and audio content. The generated signatures can provide reliable identifications despite intentional and unintentional modifications to the content.

Extracting features of audio signal content to provide reliable identification of the signals

Methods and apparatuses for performing song detection on an audio signal are described. Clips of the audio signal are classified into classes comprising music. Class boundaries of music clips are detected as candidate boundaries of a first type. Combinations including non-overlapped sections are derived. Each section meets the following conditions: 1) including at least one music segment longer than a predetermined minimum song duration, 2) shorter than a predetermined maximum song duration, 3) both starting and ending with a music clip, and 4) a proportion of the music clips in each of the sections is greater than a predetermined minimum proportion. In this way, various possible song partitions in the audio signal can be obtained for investigation.

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Beijing, China

Claus Bauer