Abstract: A method and system for learning-based assessment of the quality of an image is provided. An image quality assessment system trains an image classifier based on a training set of sample images that have quality ratings. To train the classifier, the assessment system generates a feature vector for each sample image representing various attributes of the image. The assessment system may train the classifier using an adaptive boosting technique to calculate a quality score for an image. Once the classifier is trained, the assessment system may calculate the quality of an image by generating a feature vector for that image and applying the trained classifier to the feature vector to calculate the quality score for the image.

Abstract: An implementation of a technology, described herein, for relevance-feedback, content-based image retrieval minimizes the number of iterations for user feedback regarding the semantic relevance of exemplary images while maximizing the resulting relevance of each iteration. One technique for accomplishing this is to use a Bayesian classifier to treat positive and negative feedback examples with different strategies. In addition, query refinement techniques are applied to pinpoint the users' intended queries with respect to their feedbacks. These techniques further enhance the accuracy and usability of relevance feedback. This abstract itself is not intended to limit the scope of this patent. The scope of the present invention is pointed out in the appending claims.

Abstract: Multi-label active learning may entail training a classifier with a set of training samples having multiple labels per sample. In an example embodiment, a method includes accepting a set of training samples, with the set of training samples having multiple respective samples that are each respectively associated with multiple labels. The set of training samples is analyzed to select a sample-label pair responsive to at least one error parameter. The selected sample-label pair is then submitted to an oracle for labeling.

Abstract: Various embodiments provide methods and systems for streaming data that can facilitate streaming during bandwidth fluctuations in a manner that can enhance the user experience. In one aspect, a forward-shifting technique is utilized to buffer data that is to be streamed, e.g. an enhancement layer in a FGS stream. Various techniques can drop layers actively when bandwidth is constant. The saved bandwidth can then be used to pre-stream enhancement layer portions. In another aspect, a content-aware decision can be made as to how to drop enhancement layers when bandwidth decreases. During periods of decreasing bandwidth, if a video segment does not contain important content, the enhancement layers will be dropped to keep the forward-shifting of the enhancement layer unchanged. If the enhancement layer does contain important content, it will be transmitted later when bandwidth increases.

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: Systems and methods for clustering Web queries are described. In one aspect, one or more of a same document and a plurality of similar documents selected by a user in response to a plurality of queries is identified. Responsive to this identification, a query cluster is generated. The cleric the query cluster indicates that the queries are similar independent of whether individual ones of the queries comprise similar composition with respect to other ones of the queries.

Abstract: By understanding a website author's intention through an analysis of the function of a website, website content can be adapted for presentation or rendering in a manner that more closely appreciates and respects the function behind the website. Various inventive systems and methods analyze a website's function so that its content can be adapted to different client environments, e.g. devices, network conditions, or user preferences. A novel function-based object model automatically identifies objects associated with a website, and analyzes those objects in terms of their functions. The function-based object model permits consistent, informed decisions to be made in the adaptation process, so that web content is displayed not only in an organized manner, but in a manner that reflects the author's intention.

Abstract: A method and system for generating a classifier to classify sub-objects of an object based on a relationship between sub-objects is provided. The classification system provides training sub-objects along with the actual classification of each training sub-object. The classification system may iteratively train sub-classifiers based on feature vectors representing the features of each sub-object, the actual classification of the sub-object, and a weight associated with the sub-object. After a sub-classifier is trained, the classification system classifies the training sub-objects using the trained sub-classifier. The classification system then adjusts the classifications based on relationships between training sub-objects. The classification system assigns a weight for the sub-classifier and weight for each sub-object based on the accuracy of the adjusted classifications.

Abstract: Methods and apparatuses are provided for detecting blur within digital images using Cepstrum analysis blur detection techniques that are able to detect motion blur and/or out-of-focus blur.

Abstract: Correlative multi-label image annotation may entail annotating an image by indicating respective labels for respective concepts. In an example embodiment, a classifier is to annotate an image by implementing a labeling function that maps an input feature space and a label space to a combination feature vector. The combination feature vector models both features of individual ones of the concepts and correlations among the concepts.

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: A method and system for generating 3D images of faces from 2D images, for generating 2D images of the faces at different image conditions from the 3D images, and for recognizing a 2D image of a target face based on the generated 2D images is provided. The recognition system provides a 3D model of a face that includes a 3D image of a standard face under a standard image condition and parameters indicating variations of an individual face from the standard face. To generate the 3D image of a face, the recognition system inputs a 2D image of the face under a standard image condition. The recognition system then calculates parameters that map the points of the 2D image to the corresponding points of a 2D image of the standard face. The recognition system uses these parameters with the 3D model to generate 3D images of the face at different image conditions.

Abstract: Systems and methods for a media agent are described. In one aspect, user access of a media content source is detected. Responsive to this detection, a piece of media content and associated text is collected from the media content source. Semantic text features are extracted from the associated text and the piece of media content. The semantic text features are indexed into a media database.

Abstract: Various embodiments provide methods and systems for streaming data that can facilitate streaming during bandwidth fluctuations in a manner that can enhance the user experience. In one aspect, a forward-shifting technique is utilized to buffer data that is to be streamed, e.g. an enhancement layer in a FGS stream. Various techniques can drop layers actively when bandwidth is constant. The saved bandwidth can then be used to pre-stream enhancement layer portions. In another aspect, a content-aware decision can be made as to how to drop enhancement layers when bandwidth decreases. During periods of decreasing bandwidth, if a video segment does not contain important content, the enhancement layers will be dropped to keep the forward-shifting of the enhancement layer unchanged. If the enhancement layer does contain important content, it will be transmitted later when bandwidth increases.

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: Improvements are provided to effectively assess a user's face and head pose such that a computer or like device can track the user's attention towards a display device(s). Then the region of the display or graphical user interface that the user is turned towards can be automatically selected without requiring the user to provide further inputs. A frontal face detector is applied to detect the user's frontal face and then key facial points such as left/right eye center, left/right mouth corner, nose tip, etc., are detected by component detectors. The system then tracks the user's head by an image tracker and determines yaw, tilt and roll angle and other pose information of the user's head through a coarse to fine process according to key facial points and/or confidence outputs by pose estimator.

Abstract: By understanding a website author's intention through an analysis of the function of a website, website content can be adapted for presentation or rendering in a manner that more closely appreciates and respects the function behind the website. Various inventive systems and methods analyze a website's function so that its content can be adapted to different client environments, e.g. devices, network conditions, or user preferences. A novel function-based object model automatically identifies objects associated with a website, and analyzes those objects in terms of their functions. The function-based object model permits consistent, informed decisions to be made in the adaptation process, so that web content is displayed not only in an organized manner, but in a manner that reflects the author's intention.

Abstract: The disclosed subject matter improves iterative results of content-based image retrieval (CBIR) using a bigram model to correlate relevance feedback. Specifically, multiple images are received responsive to multiple image search sessions. Relevance feedback is used to determine whether the received images are semantically relevant. A respective semantic correlation between each of at least one pair of the images is then estimated using respective bigram frequencies. The bigram frequencies are based on multiple search sessions in which each image of a pair of images is semantically relevant.

Abstract: A method and system for generating 3D images of faces from 2D images, for generating 2D images of the faces at different image conditions from the 3D images, and for recognizing a 2D image of a target face based on the generated 2D images is provided. The recognition system provides a 3D model of a face that includes a 3D image of a standard face under a standard image condition and parameters indicating variations of an individual face from the standard face. To generate the 3D image of a face, the recognition system inputs a 2D image of the face under a standard image condition. The recognition system then calculates parameters that map the points of the 2D image to the corresponding points of a 2D image of the standard face. The recognition system uses these parameters with the 3D model to generate 3D images of the face at different image conditions.

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.