Abstract: A method providing real-time popularity information regarding TV programs, performed during a short period of time at a server with one or more processors and memory. The server receives current TV viewing information from a plurality of distinct households. The current TV viewing information for a household identifies one or more TV programs that are now showing at the household. The server aggregates the current TV viewing information, thereby identifying one or more currently popular TV programs. The currently popular TV programs have more household viewers than less popular TV programs. The server receives a request from a household seeking identification of currently popular TV programs. The server selects one or more of the currently popular TV programs identified during the aggregation, and sends information to the household. The information identifies the selected one or more currently popular TV programs.

Abstract: A server receives an IP address associated with an account of a TV subscriber using a TV service. The IP address is associated with a set top box employed by the TV subscriber to display TV content provided by the TV service. The IP address is also associated with computers of a household corresponding to the TV subscriber. The computers use web browsers to view Internet content. The server receives information on TV viewing, including the IP address. The server also receives information on web browsing activity in the household associated with the IP address. The information includes the IP address. The server maintains a TV log of the TV viewing and maintains an Internet log of the web browsing activity in the household associated with the IP address. The server associates entries in the TV log with entries in the Internet log(using IP address), and stores the associations.

Abstract: A method of generating model data representative of a model in a three-dimensional space of an object from input signals representative of a set of images of the object taken from a plurality of respective camera positions includes the steps of displaying a model image derived from the model data and having a plurality of primitives for viewing by a user, receiving at least one primitive selection signal responsive to user actuation of an input whereby each primitive selection signal identifies a respective selected primitive of the model, and defining a plurality of virtual cameras in the three dimensional space having positions and look directions relative to the model which correspond substantially to those of the respective actual cameras relative to the object.

Abstract: In an image processing apparatus, a face recognizer is trained using images of one or more faces to generate representation data for the face recognizer characterising the face(s). Face recognition processing is then performed using the representation data. The training and face recognition processing is performed taking into account a person's age.

Abstract: A communications system is described in which a plurality of mobile phones are provided, each including means for generating a user interface for enabling users to identify points in images as feature points. All of the phones are then operable to utilise points identified by users to generate 3D models of individuals in the images. The 3D models are generated by associating stored average depth data for points corresponding to the co-ordinates of the feature points and further points whose position is identified relative to the co-ordinates of the feature points. The 3D models are then used to generate images which are displayed on the mobile phones.

Abstract: A modelling system is provided in which a model generation computer (3) stores within a model database (17) a plurality of principle component analysis models (18-1-18n) for modelling individuals. The principle component analysis models (18-1-18-n) are generated from data sets of individuals sharing identifying characteristics e.g. the same gender/ethnicity/age etc. When a new image is to be modelled using the system, characterising data for the new individual is received together with an image of that individual. The characterising data is used to select from the model database (17) a principle component analysis model (18-1-18-n) where the principle component analysis model selected comprises a model generated utilising images of individuals sharing the identifying characteristics corresponding to the characterisation data for the individual to be modelled.

Abstract: In order to avoid the generation of blurred images principle component analysis models (21) are generated by identifying points in the images outlining facial features in the images and creating a triangulation of the face of an individual in which boundaries of the facial features of an individual lie substantially along the edges of triangles in the triangulation. A principle component analysis model (21) is then created using the variation in coordinates of the points forming the triangulation and the differences in image data of the images divided by the triangulations. As the edges of facial features tend to lie along edges of the triangles, morphing of these shapes does not cause these features to be stretched across two triangles and hence variation in facial features such as the shape of eyebrows or eyes is primarily encoded in the variation of location of the vertices of the triangulation rather than differences in the generated morphed images used to determine coloring for generated models.

Abstract: A gaze tracking system (1,3,8) is provided which obtains images of an operator (9) and processes the images to associate the images with coordinates of where the operators gaze is directed towards. In order to identify images where an operator is looking in the same direction, images obtained by a camera (8) are first processed using the retinex algorithm. Image patches from the processed image are then compared with stored feature images and an initial classification based upon the correspondence between areas of the processed image and the stored feature images is determined. This initial classification is then further processed and each image is assigned a single classification. The areas identified by different classifications are then determined so that classifications assigned to adjacent images identify points closer together and classifications never assigned to an adjacent images identify points further apart.

Abstract: Three-dimensional computer model data, moving image data or still image data showing at least one person is stored in an archive database 126, 703, 850, 1303, together with additional information to improve the searching and retrieval of data therefrom. The additional information includes view parameter data 512, 1040 which defines at whom or what each person is looking during each predetermined period of time or image. Text data 504, 1020 which comprises words associated with the person, and viewing histogram data 540 which, for each period of text data defines the percentage of time that the speaking person spent looking at each other person or object, may also be stored.

Abstract: Image data from cameras showing movement of a number of people, and sound data, is archived and processed to determine the position and orientation of each person's head and to determine at whom each person is looking. The speaker is determined by determining at which person most people are looking. Alternatively, the sound data is processed to determine the direction from which the sound came, and it is determined who is speaking by determining which person's head is in a position corresponding to the direction from which the sound came. The personal speech recognition parameters for the speaker are selected and used to convert the sound data to text data. Image data to be archived is chosen by selecting the camera which best shows the speaker and the participant to whom he is speaking. Data is stored in a meeting archive database.

Abstract: Image data from a plurality of cameras 2-1, 2-2, 2-3 showing the movements of a number of people, for example in a meeting, and sound data from a directional microphone array 4 is processed by a computer processing apparatus 24 to archive the data in a meeting archive database 60. The image data is processed to determine the three-dimensional position and orientation of each person's head and to determine at whom each person is looking. The sound data is processed to determine the direction from which the sound came. Processing is carried out to determine who is speaking by determining which person has his head in a position corresponding to the direction from which the sound came. Having determined which person is speaking, the personal speech recognition parameters for that person are selected and used to convert the sound data to text data. Image data to be archived is chosen by selecting the camera which best shows the speaking participant and the participant to whom he is speaking.

Abstract: A communications system is described in which a plurality of mobile phones are provided, each including means for generating a user interface for enabling users to identify points in images as feature points. All of the phones are then operable to utilise points identified by users to generate 3D models of individuals in the images. The 3D models are generated by associating stored average depth data for points corresponding to the co-ordinates of the feature points and further points whose position is identified relative to the co-ordinates of the feature points. The 3D models are then used to generate images which are displayed on the mobile phones.

Abstract: In a processing system, video images of moving objects are processed to model the objects in a 3D computer model. Video from multiple cameras is processed to separate objects from their shadows, and to test whether an object is made up of separate objects, which are then modelled separately. Each object is modelled using vertical planes whose bases approximate the object's ground footprint, using planes based on object surface planes identified in the image data, or using a single vertical plane. Pixel data from the video images is rendered onto the planes in the models. The video for rendering is selected based on the viewer's viewing direction, the camera viewing directions, and quality characteristics of the cameras and image data. If the viewer's viewing direction is close to vertical or a plane of an object, a schematic of the objects' positions is displayed. To account for image data from different cameras being used, successive images are tested for visual discontinuous, and are modified if necessary.

Abstract: A 3D computer model of an object is generated by calculating the intersections of polyhedra. Each polyhedron defines a volume of 3D space containing at least part of the object. The 3D points of intersection of the planar faces of the polyhedra are calculated and each point is labeled with the planar faces which meet thereat. The points are connected to form a polygon mesh using the labels to determine which points should be connected together. In calculating the points, a volume containing the object is subdivided into parts, each part is tested against the polyhedra and then discarded, subdivided further, or the point of intersection of planar faces within the volume part is calculated. A volume part is discarded if it is outside at least one polyhedron. The volume part is subdivided into further parts if it is intersected by more than a predetermined number of polyhedra faces.

Abstract: A 3-D model of an object is created by processing images taken from a series of camera positions. An initial sequence of the images is processed to define respective image co-ordinates of matching features to generate a set of model data defining model points in a 3-D space of the model and to obtain respective camera solutions representative of positions and orientations of virtual cameras in the 3-D space defining views of the model corresponding to the images. A new image is added to the sequence and processed to obtain a camera solution for a corresponding new virtual camera for use in generating further model data.

Abstract: A gaze tracking system (1,3,8) is provided which obtains images of an operator (9) and processes the images to associate the images with coordinates of where the operators gaze is directed towards.

Abstract: In an apparatus and method for creating a three-dimensional model of an object, images of the object taken from different, unknown positions are processed to identify the points in the images which correspond to the same point on the actual object (that is “matching” points), the matching points are used to determine the relative positions from which the images were taken, and the matching points and calculated positions are used to calculate points in a three-dimensional space representing points on the object. A number of different techniques are used to identify the matching points, and a number of solutions are calculated and tested for the relative positions, the solution which is consistent with the largest number of matching points being selected.

Abstract: In an apparatus and method for creating a three-dimensional model of an object, images of the object taken from different, unknown positions are processed to identify the points in the images which correspond to the same point on the actual object (that is “matching” points), the matching points are used to determine the relative positions from which the images were taken, and the matching points and calculated positions are used to calculate points in a three-dimensional space representing points on the object. A number of different techniques are used to identify the matching points, and a number of solutions are calculated and tested for the relative positions.

Abstract: In order to avoid the generation of blurred images principle component analysis models (21) are generated by identifying points in the images outlining facial features in the images and creating a triangulation of the face of an individual in which boundaries of the facial features of an individual lie substantially along the edges of triangles in the triangulation. A principle component analysis model (21) is then created using the variation in coordinates of the points forming the triangulation and the differences in image data of the images divided by the triangulations. As the edges of facial features tend to lie along edges of the triangles, morphing of these shapes does not cause these features to be stretched across two triangles and hence variation in facial features such as the shape of eyebrows or eyes is primarily encoded in the variation of location of the vertices of the triangulation rather than differences in the generated morphed images used to determine colouring for generated models.

Abstract: A communications system is described in which a plurality of mobile phones are provided, each including means for generating a user interface for enabling users to identify points in images as feature points. All of the phones are then operable to utilise points identified by users to generate 3D models of individuals in the images. The 3D models are generated by associating stored average depth data for points corresponding to the co-ordinates of the feature points and further points whose position is identified relative to the co-ordinates of the feature points. The 3D models are then used to generate images which are displayed on the mobile phones.