Abstract:
A method and apparatus are disclosed for recommending items of interest to a user, such as television program recommendations, before a viewing history or purchase history of the user is available. A third party viewing or purchase history is processed to generate stereotype profiles that reflect the typical patterns of items selected by representative viewers. A user can select the most relevant stereotype(s) from the generated stereotype profiles and thereby initialize his or her profile with the items that are closest to his or her own interests. A clustering routine partitions the third party viewing or purchase history (the data set) into clusters using a k-means clustering algorithm, such that points (e.g., television programs) in one cluster are closer to the mean of that cluster than any other cluster. The value of k is incremented in accordance with a measure of cluster compactness.
Abstract:
A method and apparatus are disclosed for generating and maintaining enhanced background models for use in background-foreground segmentation. Background models are modified to contain an indication of objects that are typically stationary. Thereafter, if an object moves and has been previously identified as an object that is typically stationary, the object will not unnecessarily be identified as part of the foreground during background-foreground segmentation. In an exemplary implementation, moving objects are classified into two sets. A first set includes objects that typically move independently and a second set includes objects that are typically stationary. Generally, once an object is assigned to the second (stationary object) set, the object will remain in the background, even if the object is moved (normally, movement of the object would cause the object to become part of the foreground).
Abstract:
A process for adaptive bookmarking of often-visited web sites, comprising the steps of (a) optionally determining the identity of a particular user, (b) determining whether a webpage has been detected, (c) if the webpage in step (b) has been detected, determining whether the webpage has been previously visited by a particular user, (d) performing one of (i) creating an initial record of the webpage visit by the particular user if it has been determined in step (c) that the webpage has not been previously visited by the particular user, and (ii) determining whether the webpage has been previously bookmarked if it has been determined in step (c) that the webpage has been previously visited by the particular user, (e) updating a visitation count if it has been determined in step (c) that the webpage has been previously visited by the particular user, (f) determining whether the visitation count has reached a predetermined threshold; and (g) recommending the bookmarking of the address of the webpage if it determined in step (f) that the predetermined threshold of the visitation count has been reached. The visitation count may be number of plural visits and time spent visiting. The system may either automatically purge bookmarks or do so by recommendation after non-use for predetermined periods of time. A system includes hardware plus a program module to perform the bookmarking functions.
Abstract:
A system and method for alerting a driver of an automobile to a traffic condition. The system comprises at least one camera having a field of view and facing in the forward direction of the automobile. The camera captures images of the field of view in front of the automobile. A control unit receives images of the field of view from the camera and identifies objects therein of a predetermined type. The control unit analyzes the object images of at least one predetermined type to determine whether one or more of the identified objects present a condition that requires the driver's response. A display receives control signals from the control unit regarding the one or more of the objects that present a condition that requires the driver's response. The display displays an image of the object to the driver that is positioned and scaled so that it overlays the actual object as seen by the driver, the displayed image of the object enhancing a feature of the actual object to alert the driver.
Abstract:
A method and system for providing a mood based virtual photo album which provides photos based upon a sensed mood the viewer. The method may include the steps of capturing a first image of a facial expression of a viewer by a camera, providing the image to a pattern recognition module of a processor, determine a mood of the viewer by comparing the facial expression with a plurality of previously stored images of facial expressions having an associated emotional identifier that indicates a mood of each of the plurality of previously stored images, retrieving a set of photos from storage for transmission to the viewer based on the emotional identifier associated with the determined mood, and transmitting the set of photos in the form of an electronic photo album. A system includes a camera, a user interface for transmitting a first image of a facial expression of a viewer captured by the camera, a processor for receiving the transmitted image by the user interface, and including a pattern recognition module for comparing the image received by the processor with a plurality of images of facial expressions from a storage area to determine a mood of the viewer. A retrieval unit retrieves a set of electronic photos corresponding to the mood of the viewer, and transmits the set of electronic photos for display as a virtual photo album.
Abstract:
A method and apparatus are disclosed for recommending items of interest to a user, such as television program recommendations, before a viewing history or purchase history of the user is available. A third party viewing or purchase history is processed to generate stereotype profiles that reflect the typical patterns of items selected by representative viewers. A user can select the most relevant stereotype(s) from the generated stereotype profiles and thereby initialize his or her profile with the items that are closest to his or her own interests. A clustering routine is disclosed to partition the third party viewing or purchase history (the data set) into clusters, such that points (e.g., television programs) in one cluster are closer to the mean of that cluster than any other cluster. A mean computation routine is also disclosed to compute the symbolic mean of a cluster.
Abstract:
A method and apparatus are disclosed for recommending items of interest to a user, such as television program recommendations, based on the viewing or purchase history of a selected third party. A viewing history of a selected third party is partitioned into a set of similar clusters. A given cluster corresponds to a segment of television programs exhibiting a specific pattern. A user can select one or more clusters from the clustered third party viewing history to supplement or replace corresponding portions (clusters) of the user's own viewing history to produce a modified viewing history. The modified viewing history is processed to generate a user profile that characterizes the viewing preferences of the user, as well as the selected viewing preferences of the third party. Program recommendations are generated using the modified user profile.
Abstract:
This invention provides an alarm system and method for adjusting the wake-up signals. The system includes a means for tracking the behavior of a person in a predetermined area under surveillance after the activation of an alarm clock, and a means for determining whether the person is motionless for a predetermined time period. Upon recognition that the observed behavior indicates the person is still sleeping, the wake-up signals are gradually increased. At the same time, the electrical power supplied to a plurality of electronic devices may be increased to assist the person to wake up.
Abstract:
A multiple viewing program recommendation system employing a commercial detection module and a multiple viewing module is disclosed. In response to a generation of viewing recommendations of two or more program during the same time slot, the multiple viewing module controls a display of a recommended program having the highest viewing priority on a television screen while the recommended program is being aired on one of the television channels until the commercial detection module detects a commercial being aired on the television channel. In response to the detection of the commercial by the commercial detection module (37), the multiple viewing module controls a display of an additional recommended program having the next highest viewing priority on the television screen while the additional recommended program is being aired on another one of the television channels.
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.