Abstract: The claimed subject matter provides for systems and/or methods for identification of instances of an object of interest in 2D images by creating a database of 3D curve models of each desired instance and comparing an image of an object of interest against such 3D curve models of instances. The present application describes identifying and verifying the make and model of a car from a possibly single image—after the models have been populated with training data of test images of many makes and models of cars. In one embodiment, an identification system may be constructed by generating a 3D curve model by back-projecting edge points onto a visual hull reconstruction from silhouettes of an instance. The system and methods employ chamfer distance and orientation distance provides reasonable verification performance, as well as an appearance model for the taillights of the car to increase the robustness of the system.

Abstract: In one embodiment, a video processing system 300 may filter a video data set to correct skew and wobble using a central processing unit 220 and a graphical processing unit 230. The video processing system 300 may apply a rolling shutter effect correction filter to an initial version of a video data set. The video processing system 300 may simultaneously apply a video stabilization filter to the initial version to produce a final version video data set.

Abstract: The description relates to sentence autocaptioning of images. One example can include a set of information modules and a set of sentence generation modules. The set of information modules can include individual information modules configured to operate on an image or metadata associated with the image to produce image information. The set of sentence generation modules can include individual sentence generation modules configured to operate on the image information to produce a sentence caption for the image.

Abstract: The description relates to sentence autocaptioning of images. One example can include a set of information modules and a set of sentence generation modules. The set of information modules can include individual information modules configured to operate on an image or metadata associated with the image to produce image information. The set of sentence generation modules can include individual sentence generation modules configured to operate on the image information to produce a sentence caption for the image.

Abstract: Image search results are obtained by providing weights to visual features to emphasize features corresponding to objects of interest while simultaneously deemphasizing irrelevant or inconsistent features that lead to poor search results. In order to minimize the impact of visual features that are unreliable or irrelevant with respect to the objects of interest in the image, context-dependent weights are provided to detect visual features such that those visual features pertaining to the objects of interest are more heavily weighted than those visual features that pertain to irrelevant or unreliable portions of the image. Visual features may be weighted for images in a searchable database. Training data may be obtained and used in weighting visual features in a query image and, alternatively, in searchable database images.

Abstract: Text in web pages or other text documents may be classified based on the images or other objects within the webpage. A system for identifying and classifying text related to an object may identify one or more web pages containing the image or similar images, determine topics from the text of the document, and develop a set of training phrases for a classifier. The classifier may be trained and then used to analyze the text in the documents. The training set may include both positive examples and negative examples of text taken from the set of documents. A positive example may include captions or other elements directly associated with the object, while negative examples may include text taken from the documents, but from a large distance from the object. In some cases, the system may iterate on the classification process to refine the results.

Abstract: A system and method are disclosed for automatically generating a highlight reel of video content. Segments from a segment list may be associated with, or indexed to, corresponding sequences from a video of an event for which the segment list is prepared. Thereafter, also using the segment list, segments may be scored using a variety of predefined criteria to come up with segments which are likely to be of greatest interest to a particular user. The video sequences associated with the highest scored segments are used as the video highlight reel.

Abstract: The claimed subject matter provides for systems and/or methods for identification of instances of an object of interest in 2D images by creating a database of 3D curve models of each desired instance and comparing an image of an object of interest against such 3D curve models of instances. The present application describes identifying and verifying the make and model of a car from a possibly single image—after the models have been populated with training data of test images of many makes and models of cars. In one embodiment, an identification system may be constructed by generating a 3D curve model by back-projecting edge points onto a visual hull reconstruction from silhouettes of an instance. The system and methods employ chamfer distance and orientation distance provides reasonable verification performance, as well as an appearance model for the taillights of the car to increase the robustness of the system.

Abstract: A UE receives HSDPA traffic comprising legacy HSDPA traffic and HS-SCCH-less HSDPA traffic. The UE concurrently processes the received legacy HSDPA traffic and the received HS-SCCH-less HSDPA traffic. The received HSDPA traffic is concurrently buffered into a first storage and a second storage to support simultaneously receiving legacy HSDPA traffic and HS-SCCH-less HSDPA traffic. A HARQ process is performed on the buffered HSDPA traffic in the first storage or the second storage according to a corresponding HS-SCCH CRC test. The resulting HARQ processed HSDPA traffic is Turbo decoded. Turbo decoding on the previously HARQ processed HSDPA traffic is performed simultaneously with HARQ processing on the buffered HSDPA traffic in the first storage or the second storage. The buffered HS-SCCH-less HSDPA traffic is processed via HARQ processing and Turbo decoding for each of the four pre-determined transport formats.

Abstract: A system and method are disclosed for quickly and easily browsing to points of interest within a recorded video. In examples, the present system works in tandem with a segment list which includes a list of different video sequences of a stored video of an event. One typical example of a segment list is a play-by-play (PBP) which is prepared contemporaneously with a sporting event. Segments from a segment list may be associated with, or indexed to, corresponding sequences from the stored video. Thereafter, a user interface allows a user to interactively watch or browse the event by jumping to a desired point in the video for playback by selecting its associated segment from the user interface.

Abstract: Disclosed herein are representative embodiments of tools and techniques for setting color settings of an operating system using one or more photographs. According to one exemplary technique, a photograph is received, and one or more pixel weights for one or more pixels of the photograph are determined. Also, using at least one of the one or more pixel weights, at least one dominant color of the photograph is determined. Additionally, using the at least one dominant color, at least one color setting of an operating system is set.

Abstract: A UE receives a HS-PDSCH transmission from a base station and concurrently performs rate matching on systematic bits and parity bits (parity 1 bits, parity 2 bits) of the received HS-PDSCH transmission. The systematic bits and parity bits are buffered in a CPC circular buffer to support HARQ processing in a HS-SCCH-less operation of the base station. Memory locations are computed for the systematic bits and the parity bits according to corresponding transmission parameters such as, for example, redundancy version, number of systematic bits and/or number of physical channels. The systematic bits and the parity bits are stored in the corresponding computed memory locations of the CPC circular buffer. At least a portion of the stored systematic bits and parity bits are concurrently generated based on corresponding transmission parameters from the CPC circular buffer per request to support concurrent rate matching on systematic bits and parity bits.

Abstract: The description relates to sentence autocaptioning of images. One example can include a set of information modules and a set of sentence generation modules. The set of information modules can include individual information modules configured to operate on an image or metadata associated with the image to produce image information. The set of sentence generation modules can include individual sentence generation modules configured to operate on the image information to produce a sentence caption for the image.

Abstract: Disclosed herein are representative embodiments of tools and techniques for setting color settings of an operating system using one or more photographs. According to one exemplary technique, a photograph is received, and one or more pixel weights for one or more pixels of the photograph are determined. Also, using at least one of the one or more pixel weights, at least one dominant color of the photograph is determined. Additionally, using the at least one dominant color, at least one color setting of an operating system is set.

Abstract: Text in web pages or other text documents may be classified based on the images or other objects within the webpage. A system for identifying and classifying text related to an object may identify one or more web pages containing the image or similar images, determine topics from the text of the document, and develop a set of training phrases for a classifier. The classifier may be trained and then used to analyze the text in the documents. The training set may include both positive examples and negative examples of text taken from the set of documents. A positive example may include captions or other elements directly associated with the object, while negative examples may include text taken from the documents, but from a large distance from the object. In some cases, the system may iterate on the classification process to refine the results.

Abstract: In one embodiment, a video processing system 300 may filter a video data set to correct skew and wobble using a central processing unit 220 and a graphical processing unit 230. The video processing system 300 may apply a rolling shutter effect correction filter to an initial version of a video data set. The video processing system 300 may simultaneously apply a video stabilization filter to the initial version to produce a final version video data set.

Abstract: Modified microorganisms are prepared by inactivation of the endogenous lactate dehydrogenase gene. The microorganisms are deposited under NCIMB Accession Nos. 41277, 41278, 41279, 41280 or 41281.

Abstract: Text in web pages or other text documents may be classified based on the images or other objects within the webpage. A system for identifying and classifying text related to an object may identify one or more web pages containing the image or similar images, determine topics from the text of the document, and develop a set of training phrases for a classifier. The classifier may be trained and then used to analyze the text in the documents. The training set may include both positive examples and negative examples of text taken from the set of documents. A positive example may include captions or other elements directly associated with the object, while negative examples may include text taken from the documents, but from a large distance from the object. In some cases, the system may iterate on the classification process to refine the results.

Abstract: Image search results are obtained by providing weights to visual features to emphasize features corresponding to objects of interest while simultaneously deemphasizing irrelevant or inconsistent features that lead to poor search results. In order to minimize the impact of visual features that are unreliable or irrelevant with respect to the objects of interest in the image, context-dependent weights are provided to detect visual features such that those visual features pertaining to the objects of interest are more heavily weighted than those visual features that pertain to irrelevant or unreliable portions of the image. Visual features may be weighted for images in a searchable database. Training data may be obtained and used in weighting visual features in a query image and, alternatively, in searchable database images.

Abstract: Text in web pages or other text documents may be classified based on the images or other objects within the webpage. A system for identifying and classifying text related to an object may identify one or more web pages containing the image or similar images, determine topics from the text of the document, and develop a set of training phrases for a classifier. The classifier may be trained and then used to analyze the text in the documents. The training set may include both positive examples and negative examples of text taken from the set of documents. A positive example may include captions or other elements directly associated with the object, while negative examples may include text taken from the documents, but from a large distance from the object. In some cases, the system may iterate on the classification process to refine the results.