Abstract: Disclosed is a method and system for controlling access to a television set using a remote control unit having a finger verification means. The method includes the steps of: placing at least one finger on the remote control unit for scanning; obtaining fingerprint data indicative of the scanned finger; comparing the fingerprint data to predetermined reference data to establish a fingerprint match; and, if a match is established, providing access to a number of channels associated with the scanned finger. The system includes a fingerprint reader for generating fingerprint data; a processor programmed to prompt the user to enter fingerprint data; and, a fingerprint recognition means for verifying that the user is an authorized user of the remote control apparatus.

Abstract: Method and system of detecting and analyzing the presence of a logo in one or more datastreams. In the method, at least one video datastream of an event is first received. Next, one or more regions of interest (ROIs) for the logo in one or more images comprising the at least one datastream are identified. The one or more ROIs are analyzed to detect if the logo is present in the ROI. If so, the detection of the presence of the logo is used in making either a broadcasting decision or an advertising decision.

Abstract: A method and apparatus are disclosed for monitoring a location using vision-based technologies and to automatically trigger the activation of a child safety feature or an alarm when a child is detected. One or more image capture devices are focused on a given location. The captured images are processed to identify the presence of a child and to initiate an appropriate response, such as sending assistance, activating a child safety feature or triggering an alarm. A number of rules can be utilized to define various child safety events. Each rule contains one or more conditions that must be satisfied in order for the rule to be triggered, and, optionally, a corresponding action-item that should be performed when the rule is satisfied, such as sending assistance, activating a child safety feature or triggering an alarm.

Abstract: Generally, an Eigen network and system using same are disclosed that use Principal Component Analysis (PCA) in a middle (or “hidden”) layer of a neural network. The PCA essentially takes the place of a Radial Basis Function hidden layer. A classifier comprises inputs that are routed to a PCA device. The PCA device performs PCA on the inputs and produces outputs (entitled “PCA outputs” for clarity). The PCA outputs are connected to output nodes. Generally, each output is connected to each output node. Each connection is multiplied by a weight, and each output node uses weighted PCA outputs to produce an output (entitled a “node output” for clarity). These node outputs are then generally compared in order to assign a class to the input. A system uses the PCA classifier to classify input patterns. In a third aspect of the invention, a PCA classifier is trained in order to determine weights for each of the connections that are connected to the output nodes.

Abstract: The present invention relates to a control system and method for automatically adjusting the viewing condition to enhance the experiences associated with watching a television program. The system includes a unit for deriving a classification of each video signal received therein, a unit for observing a viewer's facial expression, and a unit for processing the output of the observed facial expression to determine whether the observed facial expression is associated with predefined facial expressions stored in a recognition module. Based on the classification and/or if there is a match between the observed facial expression with the at least one of the predefined facial expressions, the electrical power supplied to any one of electrical devices provided in the room is varied according to predetermined criteria.

Abstract: A system and method for classifying facial images from a partial view of a facial image, the method comprising the steps of: training a classifier device for recognizing facial images, the classifier device being trained with input data associated with a facial image of a subject; detecting a partial view of a subject's facial image; warping the partial view of the subject's facial image onto a frontal image to obtain a warped image of the subject; and, classifying the warped image according to a classification method performed by the trained classifier device.

Abstract: Linear method for performing head motion estimation from facial feature data, the method comprising the steps of: obtaining first facial image and detecting a head in the first image; detecting position of four points P of said first facial image where P={p1, p2, p3, p4}, and pk=(xk, yk); obtaining second facial image and detecting a head in the second image; detecting position of four points P′ of the second facial image where P′={p1′, p2′, p3′, p4′} and pk′=(xk′, yk′); and, determining the motion of the head represented by a rotation matrix R and translation vector T using the points P and P′.

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: A system and method for classifying facial image data, the method comprising the steps of: training a classifier device for recognizing facial images and obtaining learned models of the facial images used for training; inputting a vector of a facial image to be recognized into the classifier, the vector comprising data content associated with one-half of a full facial image; and, classifying the one-half face image according to a classification method. Preferably, the classifier device is trained with data corresponding to one-half facial images, the classifying step including matching the input vector of one-half image data against corresponding data associated with each resulting learned model.

Abstract: Cameras and image processing techniques are applied to the problem of spill detection. Fixed background data may be removed using a technique based on image subtraction. The remainder of one or more images may be segmented. The segments may then be tested to identify and remove from further analysis segments corresponding to non-spill foreground objects, for example by forming luminance and/or chrominance profiles to detect the presence of a high rate of specular albido that would be associated with a wet spill. Further testing may be done, for example by determining if a segment corresponds to a planar object lying in the plane of the floor using planar projection transforms and multiple cameras. If a segment is likely to indicate a spill, a notification may be generated.

Abstract: A system and method for classifying facial images from a temporal sequence of images, comprises the steps of: training a classifier device for recognizing facial images, the classifier device being trained with input data associated with a full facial image; obtaining a plurality of probe images of the temporal sequence of images; aligning each of the probe images with respect to each other; combining the images to form a higher resolution image; and, classifying said higher resolution image according to a classification method performed by the trained classifier device.

Abstract: A method and apparatus are disclosed for automatically learning and identifying events in image data using hierarchical HMMs to define and detect one or more events. The hierarchical HMMs include multiple paths that encompass variations of the same event. Hierarchical HMMs provide a framework for defining events that may be exhibited in various ways. Each event is modeled in the hierarchical HMM with a set of sequential states that describe the paths in a high-dimensional feature space. These models can then be used to analyze video sequences to segment and recognize each individual event to be recognized. The hierarchical HMM is generated during a training phase, by processing a number of images of the event of interest in various ways, typically observed from multiple viewpoints.

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: A method for monitoring a person of interest in a scene, the method comprising: capturing image data of the scene; detecting and tracking the person of interest in the image data; analyzing features of the person of interest; and detecting at least one of an event and behavior associated with the detected person of interest based on the features; and informing a third party of the at least one detected events and behavior.

Abstract: System and method for adjusting the position of a displayed image of a person. The system comprises a control unit that receives a sequence of images and processes the received images to determine whether the person is positioned at the border of the received images to be displayed. If so positioned, the control unit generates control signals to control the position of an optical device providing the sequence of images so that the person is positioned entirely within the image.

Abstract: A method for aiding a customer in the purchase of clothes on-line. The method including: accessing an Internet web site for the purchase of clothes, the Internet web site having a three-dimensional model of at least one style and size of clothes displayed thereon; providing a three-dimensional model of the customer; selecting the at least one style and size of clothes displayed at the Internet web site; generating a virtual three-dimensional model of the customer wearing the at least one style and size of clothes selected; and displaying the virtual three-dimensional model to the customer.

Abstract: A method for presenting information from telephone messages to a user. The method including the steps of: receiving incoming telephone messages; recognizing speech in the incoming telephone messages by searching the incoming telephone messages for at least one predetermined category of information; and if the at least one predetermined category of information is found in the recognized speech, presenting the at least one predetermined category of information to the user.

Abstract: A method for automatically assessing interest in a displayed product is provided. The method including: capturing image data within a predetermined proximity of the displayed product; identifying people in the captured image data; and assessing the interest in the displayed product based upon the identified people. In a first embodiment, the identifying step identifies the number of people in the captured image data and the assessing step assesses the interest in the displayed product based upon the number of people identified. In a second embodiment, the identifying step recognizes the behavior of the people in the captured image data and the assessing step assesses the interest in the displayed product based upon the recognized behavior of the people. The method can also include the step of recognizing at least one characteristic of the people identified, which can be performed with or without the assessing step.

Abstract: A method for classification of objects in video image data. The method including the steps of: detecting moving objects in the image data; extracting two or more features from each detected moving object in the image data; classifying each moving object for each of the two or more features according to a classification method; and deriving a classification for each moving object based on the classification method for each of the two or more features. Also provided is an apparatus for classification of objects in video image data.

Abstract: A vision system that is capable of computing the crowd density at an exhibition-like event provides real-time information to visitors to allow them to avoid crowds or identify the most popular exhibits. Well-known counting techniques may be employed. One type of display that provides crowd information is a map display with an overlay showing density of visitors.