Abstract: Systems and methods for automatic generation of a browsing path across image content to present areas with high attention value are described. In particular, an image is modeled via multiple visual attentions to create a respective set of attention objects for each modeled attention. The attention objects and their respective attributes are analyzed to generate a browsing path to select ones of the attention objects. The browsing path is generated to optimize the rate of information gain from the attention objects as a function of information unit cost in terms of time constraints associated with multiple image browsing modes.

Abstract: Systems and methods for extracting a music snippet from a music stream are described. In one aspect, one or more music sentences are extracted from the music stream. The one or more sentences are extracted as a function of peaks and valleys of acoustic energy across sequential music stream portions. The music snippet is selected based on the one or more music sentences.

Abstract: Systems and methods for image attention analysis are described. In one aspect, image attention is modeled by preprocessing an image to generate a quantized set of image blocks. A contrast-based saliency map for modeling one-to-three levels of image attention is then generated from the quantized image blocks.

Abstract: An exemplary system includes a browser to browse a web page based on a web page definition having a slicing tree defining an arrangement of rectangular regions in the web page. The web page definition can include parametric data describing adaptability parameters associated with a rectangular region. A rendering module renders an adapted web page based on the web page definition, and a proxy module generates an intermediary adapted web page definition. A method includes rendering the web page according to a slicing tree and block property data in an associated web page definition. The method may include determining a set of unsummarized blocks that maximize information fidelity.

Abstract: Management of rights to content is provided within an authorized domain. In a single authorized domain, where a plurality of domain interfaces are protected using a common rights management system, a copy of particular content may be allowed to be provided on all devices or only on specific devices coupled to the domain via the interfaces. Copy protection information, for outputs to external devices not protected by the common rights management system, is also specified. Rules can be provided for specifying whether particular content may be copied or moved to another protected domain. A number of rendering devices permitted to render the content simultaneously may be specified. Content rules are provided for use in managing rights to content within an authorized domain. Such rules can be associated with content that is persistently stored by a consumer device, as well as with content that is only rendered by a consumer device.

Abstract: Red-eye detection based on red region detection with eye confirmation initially identifies pixels that correspond to the color of red-eye within an image. A determination is then made as to whether these identified pixels and surrounding areas are part of an eye or not part of an eye. Those identified pixels that are determined to be part of an eye are the detected red-eye regions.

Abstract: Red-eye detection based on red region detection with eye confirmation initially identifies pixels that correspond to the color of red-eye within an image. A determination is then made as to whether these identified pixels and surrounding areas are part of an eye or not part of an eye. Those identified pixels that are determined to be part of an eye are the detected red-eye regions.

Abstract: An image retrieval system performs both keyword-based and content-based image retrieval. A user interface allows a user to specify queries using a combination of keywords and examples images. Depending on the input query, the image retrieval system finds images with keywords that match the keywords in the query and/or images with similar low-level features, such as color, texture, and shape. The system ranks the images and returns them to the user. The user interface allows the user to identify images that are more relevant to the query, as well as images that are less or not relevant to the query. The user may alternatively elect to refine the search by selecting one example image from the result set and submitting its low-level features in a new query. The image retrieval system monitors the user feedback and uses it to refine any search efforts and to train itself for future search queries.

Abstract: Red-eye detection based on red region detection with eye confirmation initially identifies pixels that correspond to the color of red-eye within an image. A determination is then made as to whether these identified pixels and surrounding areas are part of an eye or not part of an eye. Those identified pixels that are determined to be part of an eye are the detected red-eye regions.

Abstract: Systems and methods for shape registration are described. In one aspect, training shape vectors are generated from images in an image database. The training shape vectors identify landmark points associated with one or more object types. A distribution of shape in the training shape vectors is represented as a prior of tangent shape in tangent shape space. The prior of tangent shape is then incorporated into a unified Bayesian framework for shape registration.

Abstract: A system and process for video characterization that facilitates video classification and retrieval, as well as motion detection, applications. This involves characterizing a video sequence with a gray scale image having pixel levels that reflect the intensity of motion associated with a corresponding region in the sequence of video frames. The intensity of motion is defined using any of three characterizing processes. Namely, a perceived motion energy spectrum (PMES) characterizing process that represents object-based motion intensity over the sequence of frames, a spatio-temporal entropy (STE) characterizing process that represents the intensity of motion based on color variation at each pixel location, a motion vector angle entropy (MVAE) characterizing process which represents the intensity of motion based on the variation of motion vector angles.

Abstract: Systems and methods for representing sequential motion patterns are described. In one aspect, video frames are converted into a sequence of energy redistribution measurements. One or more motion filters are then applied to the ER measurements to generate one or more temporal sequences of motion patterns, the number of temporal sequences being a function of the number of motion filters.

Abstract: In community mining based on core objects and affiliated objects, a set of core objects for a community of objects are identified from a plurality of objects. The community is expanded, based on the set of core objects, to include a set of affiliated objects. According to one aspect, a model of a community of objects is obtained by grouping a first collection of a plurality of objects into a center portion, and grouping a second collection of the plurality of objects into one or more concentric portions around the center portion. The groupings of the first and second collections of the objects are identified as the community of objects.

Abstract: Methods are provided for preparing spray-dried, drug-containing particles comprising the steps of: (a) selecting drug, an aqueous solution, and a proton-sequestering agent; (b) adding the drug and the proton-sequestering agent to the solution to form a feed solution; and (c) spray drying the feed solution to form the spray-dried, drug-containing particles, wherein at least a portion of the proton-sequestering agent remains mixed with the drug in the spray-dried, drug containing particles, particles and pharmaceutical formulations comprising the prepared particles as well as methods of use are also provided.

Abstract: Face detection techniques are provided that use a multiple-stage face detection algorithm. An exemplary three-stage algorithm includes a first stage that applies linear-filtering to enhance detection performance by removing many non-face-like portions within an image, a second stage that uses a boosting chain that is adopted to combine boosting classifiers within a hierarchy “chain” structure, and a third stage that performs post-filtering using image pre-processing, SVM-filtering and color-filtering to refine the final face detection prediction. In certain further implementations, the face detection techniques include a two-level hierarchy in-plane pose estimator to provide a rapid multi-view face detector that further improves the accuracy and robustness of face detection.

Abstract: Systems and methods for annotating a face in a digital image are described. In one aspect, a probability model is trained by mapping one or more sets of sample facial features to corresponding names of individuals. A face from an input data set of at least one the digital image is then detected. Facial features are then automatically extracted from the detected face. A similarity measure is them modeled as a posterior probability that the facial features match a particular set of features identified in the probability model. The similarity measure is statistically learned. A name is then inferred as a function of the similarity measure. The face is then annotated with the name.

Abstract: A face model having outer and inner facial features is matched to that of first and second models. Each facial feature of the first and second models is represented by plurality of points that are adjusted for each matching outer and inner facial feature of the first and second models using 1) the corresponding epipolar constraint for the inner features of the first and second models. 2) Local grey-level structure of both outer and inner features of the first and second models. The matching and the adjusting are repeated, for each of the first and second models, until the points for each of the outer and inner facial features on the respective first and second models that are found to match that of the face model have a relative offset there between of not greater than a predetermined convergence tolerance. The inner facial features can include a pair of eyes, a nose and a mouth. The outer facial features can include a pair of eyebrows and a silhouette of the jaw, chin, and cheeks.

Abstract: Improved methods and apparatuses are provided for use in face detection. The methods and apparatuses significantly reduce the number of candidate windows within a digital image that need to be processed using more complex and/or time consuming face detection algorithms. The improved methods and apparatuses include a skin color filter and an adaptive non-face skipping scheme.

Abstract: An image retrieval system performs both keyword-based and content-based image retrieval. A user interface allows a user to specify queries using a combination of keywords and examples images. Depending on the input query, the image retrieval system finds images with keywords that match the keywords in the query and/or images with similar low-level features, such as color, texture, and shape. The system ranks the images and returns them to the user. The user interface allows the user to identify images that are more relevant to the query, as well as images that are less or not relevant to the query. The user may alternatively elect to refine the search by selecting one example image from the result set and submitting its low-level features in a new query. The image retrieval system monitors the user feedback and uses it to refine any search efforts and to train itself for future search queries.

Abstract: Methods and apparatuses are provided for automatically generating video data based on still image data. Certain aspects of the video may also be configured to correspond to audio features identified within associated audio data.