Abstract: A system searches for segments among multiple publications dealing with a given topic or set of topics, and compiles these segments into a custom-created electronic-book. In a commercial environment, such custom-created e-books are offered for sale to a user or set of users who have expressed interest in the given topic or set of topics. Optionally, the system is aware of the publications that are in a user's existing library, and avoids the inclusion of redundant material in the custom-created e-book for that user.

Abstract: A method and apparatus are that restrict access to digital content to an authorized user on one or more systems using biometric watermarks. The disclosed biometric watermarking techniques allow an authorized user to be uniquely identified. Access to digital content is restricted to digital content in accordance with the present invention by embedding a biometric watermark, such as a biometric image, in the content. Thereafter, a user can only access the content if a biometric sample of the user matches the embedded biometric watermark. In one variation, the user can only access the content if the biometric sample is a live biometric sample. The embedded biometric watermark optionally includes information describing a system employed by the user to obtain the content. The user can optionally be permitted to access the content, without a biometric evaluation, if the content is on a system that has been previously authorized for the user using a biometric evaluation.

Abstract: A method and system for providing a personalized list of meetings per subject per user of the system (1), includes a system computer (4) and user computer (12) each configured for bidirectionally communicating over the Internet (8), whereby the system computer (4) is programmed to first obtain either explicitly (20) or implicitly (26) a profile listing various meeting preferences of a user, to next obtain a list of future meetings corresponding to at least a portion of the user's profile, followed by sending the user the list of recommended meetings generated, along with location specific information if requested by the user.

Abstract: A dynamic method and system for processing video source frames (e.g., a television movie) with a video processing system (VPS) that includes a processor, a memory structure, input devices, and an output display. The video source frames, which are received by the VPS from a video source, are executed by the processor. While the video source frames are being executed, a subset of the frames, called key frames, are extracted from the video source frames and stored in the memory structure. The extracting of the key frames is implemented in accordance with a frame extraction algorithm. The extracting is terminated prior to completion of execution of the video source frames. Following termination of extracting, the key frames are reviewed by a user with the output display to determine whether to watch the remainder of the video source frames. The key frames are erased after being reviewed.

Abstract: A recommendation system is disclosed that generates recommendations for one or more items based on user preferences and one or more environmental factors. The user's preferences are learned under various environmental conditions using an environmental data collection system. The observed environmental conditions may include, for example, location, characteristics of the location, weather or characteristics of the user's motion, such as a rate of movement. For each positive and negative behavioral example, a number of attributes of the selected item are classified in the user profile together with the prevailing environmental conditions. When recommending an item, the disclosed recommender retrieves the user preferences and evaluates the current environmental conditions. A recommendation score can be generated for each available item based on the user's demonstrated preferences under similar environmental conditions, such as in the same or a similar geographic area or under similar weather conditions.

Abstract: A system and method is provided for selectively activating biometric sensors (102, 104, 106) to authenticate the identity of an individual while conserving system resources. A biometric system has at least two tiers of sensors, first (102) and second tier sensors (104, 106), where the first tier sensors (102) are characteristically less sophisticated and less expensive to operate than the second tier sensors (104, 106). One or more of the second tier sensors (104, 106) are activated only after a user's biometric is successfully or unsuccessfully verified by one of the first tier sensors (102). Alternatively, the second tier sensors (104, 106) are activated in response to a user requesting a particular level of service or in response to an environmental condition. Alternatively, only those sensors are turned on which are compatible with a user's biometric profile.

Abstract: A system and apparatus are disclosed for modeling patterns of behavior of humans or other animate objects and detecting a violation of a repetitive pattern of behavior. The behavior of one or more persons is observed over time and features of the behavior are recorded in a multi-dimensional space. Over time, the multi-dimensional data provides an indication of patterns of human behavior. Activities that are repetitive in terms of time, location and activity, such as sleeping and eating, would appear as a Gaussian distribution or cluster in the multi-dimensional data. Probability distribution functions can be analyzed using known Gaussian or clustering techniques to identify repetitive patterns of behavior and characteristics thereof, such as a mean and variance. Deviations from repetitive patterns of behavior can be detected and an alarm can be triggered, if appropriate.

Abstract: Extracting and processing video content encoded in a rendered color space to be emulated by an ambient light source, comprising extracting dominant color information from a video signal and transforming the color information through unrendered color space using tristimulus primary matrices to form a second rendered color space for ambient distribution. Steps include quantizing the rendered color space to form an assigned color distribution, such as by reducing possible color states, or binning to form superpixels; and selecting a dominant color using a mode, mean, median, or weighted average of pixel chromaticities. A color of interest can be further analyzed to produce a true dominant color, and past video frames can guide selection of dominant colors in future frames.

Abstract: A transaction card 10 for use in a transaction includes a memory 15 and pressure sensors 20. The authorized user provides biometric data, such as a signature, by signing on the pressure sensors (20) using a pointer for storage in the memory (15) when the card is used for the first time. The signature is not visible on the card for added security. At the point of use of the transaction card (10), such as the point of sale, the user signs on an input device (50) such as a digital tablet, a tablet with pressure sensors or a slip of paper. This newly acquired signature (55) is compared with the signature stored on the transaction card (10), such as by displaying the stored signature out of the view of the user and comparing displayed signature with the acquired signature (55). The comparison may be performed by the service-providing associate or by a processor coupled to the input device (50).

Abstract: A system and method for classifying facial image data, the method comprising the steps of: training a classifier device for recognizing one or more facial images and obtaining corresponding learned models the facial images used for training; inputting a vector including data representing a portion of an unknown facial image to be recognized into the classifier; classifying the portion of the unknown facial image according to a classification method; repeating inputting and classifying steps using a different portion of the unknown facial image at each iteration; and, identifying a single class result from the different portions input to the classifier.

Abstract: Extracting and processing video content encoded in a rendered color space to be emulated by an ambient light source, using perceptual rules for intelligent dominant color selection. Steps include quantizing the video color space; performing dominant color extraction by using a mode, median, mean, or weighted average of pixel chromaticities; applying perceptual rules to further derive dominant chromaticities via [1] chromaticity transforms; [2] a weighted average using a pixel weighting function influenced by scene content; and [3] extended dominant color extraction where pixel weighting is reduced for majority pixels; and [4] transforming the dominant color chosen to the ambient light color space using tristimulus matrices. A color of interest can be further analyzed to produce a true dominant color, and past video frames can guide selection of dominant colors in future frames.

Abstract: A method for managing a plurality of video data stored on a storage device. The method including the steps of: determining whether sufficient storage space remains on the storage device to store a desired video content; if sufficient storage space does not exist on the storage device to store the desired video content, determining whether any video content of the plurality of video data stored on the storage device has been partially viewed; and if video content stored on the storage device has been partially viewed, deleting the partially viewed video content to make room for storage of the desired video content on the storage device.

Abstract: A method for generating a recommendation is provided. The method includes the steps of: receiving at least one of a negative and positive example from one or more other users; and determining a recommendation for a user based on at least one of the negative and positive examples. The method can further include the step of generating a user profile for the user based on previous behavior of the user, in which case the determining step can include determining the recommendation based on the negative example and the user profile. The determining step can also include the step of determining the recommendation based on both of the negative and positive examples.

Abstract: A method for enhancing a usage of a telephone (100) is provided. The method including: receiving an incoming call; detecting an ambient noise level; and enhancing the incoming call to make it more understandable by a recipient of the incoming call where the detected ambient noise level is greater than a predetermined threshold noise level. The enhancing can include automatically amplifying a loudness of the incoming call to the recipient of the incoming call and/or converting the incoming call to text and displaying the text to the recipient of the incoming call.

Abstract: Artificial intelligence applications require use of training sets containing positive and negative examples. Negative examples are chosen using distributions of positive examples with respect to a dominant feature in feature space. Negative examples should share or approximately share, with the positive examples, values of a dominant feature in feature space. This type of training set is illustrated with respect to content recommenders, especially recommenders for television shows.

Abstract: A method for displaying close-captioned text (116) associated with video is provided. The method including: determining a position on a portion of the video for display of the close-captioned text; detecting one or more attributes of the video surrounding the position; and adjusting one or more attributes of the close-captioned text based on the detected one or more attributes of the video. The method can further include displaying the close-captioned text in the portion of the video with the adjusted one or more attributes. The one or more attributes of the video surrounding the position can be selected from a list consisting of a brightness, a contrast, a color, and a content. The one or more attributes of the close-captioned text can be selected from a group consisting of a brightness, a contrast, a color, and a degree of transparency.

Abstract: Methods and apparatus are disclosed to various embodiments for recommending items (150) to an advisee such as television program recommendations, based on other user's viewing preferences (140) or profiles (160). In contrast to the state of the art, the other user's have at least one demographic in common with the advise, such as age, income or gender for example or combinations thereof. According to one aspect of the invention, recommendations may be generated before a viewing or purchase history of the advisee is available.

Abstract: A method for inserting replacement commercials into a data stream is provided. The method including: receiving the data stream; detecting at least one commercial in the data stream; determining a characteristic of program content at least prior to the at least one commercial; and replacing the at least one commercial in the data stream with a replacement commercial which is selected based at least in part on the determining.

Abstract: Extracting and processing video content encoded in a rendered color space to be emulated by an ambient light source, comprising extracting color information from a video signal and transforming the color information through unrendered color space using tristimulus primary matrices to form a second rendered color space to drive the ambient light source. Video signal decoding into frames can employ an interframe interpolation process using only color information from selected frames, such as extracting average or other color information from an selected screen regions to reduce bitstream load, and negative gamma correction helps prevent garish or inappropriate chromaticities and luminance.

Abstract: Commercials are recommended for insertion into audio and/or video programs. A two-step linking between the user (205) and a set of commercials (260, 262, 264, 266) is provided. A preference score indicates how much the user likes each of the programs (210, 212, 214, 216, 218). This can be achieved, e.g., using a program recommender (160). A commercial classifier (170) uses the advertiser's knowledge to provide a correlation factor that indicates an effectiveness of a commercial relative to a program. An effectiveness metric (E) may be obtained for each commercial that indicates the effectiveness of the commercial relative to the specific user by summing, over each program, a product of the preference score and the correlation factor.