Abstract: A video camera arrangement comprises an image capture device; a face detector for detecting human faces in the captured video material and for generating face data identifying detected occurrences of faces in the captured video material; a data handling medium by which data representing the captured images is transmitted and/or stored; and a processor for generating data to be transmitted or stored by the data handling medium in dependence on the detection of faces in the captured images.

Abstract: A display arrangement comprises an image display device having a first camera directed towards positions adopted by users viewing the display; one or more further cameras directed towards other respective locations; a face detector for detecting human faces in images captured by the cameras; and means for detecting those faces which appear in images captured by both the first camera and at least one of the further cameras.

Abstract: A display arrangement comprises an image display device having two or more sets of images for display; a camera directed towards positions adopted by users viewing the display; a face detector for detecting human faces in images captured by the camera, the face detector being arranged to detect faces in at least two face categories; and means, responsive to the a frequency of detection of categories of faces by the face detector at one or more different periods, for selecting a set of images to be displayed on the image display device at that time of day.

Abstract: A video data processing apparatus, that processes video data including a sequence of images, the apparatus including: an object tracker unit configured to detect a presence of one or more objects within an image and to track a detected object across successive images; an identity association unit configured to associate an identity with an object tracked by the object tracker unit; a counter unit configured to, for a first and second identity, count a number of images within which a tracked object associated with the first identity and a tracked object associated with the second identity have both been detected; and a similarity detector unit configured to determine whether two tracked objects are similar in appearance.

Abstract: An image processing method for selecting a subset of n (where n is two or more) images representative of a test set of images. The method includes detecting a degree of similarity between images in the test set of images so that the subset of images comprises those n images having substantially the lowest similarity with other images in the set.

Abstract: A face detection apparatus associated methodology is provided to generate an output indicating a likelihood of a region of an image containing a face. The apparatus includes a comparing device for comparing the region with face data that indicates a presence of the face and for detecting respective likelihood values indicating the likelihood of the region containing the face in a group of respective different face size. A control device is provided for modifying at least one of the group and the likelihood values based on a face size or a range of face sizes appropriate to at least one classification of the image. The control device is responsive to metadata associated with the image that define the at least one classification of the image. The image is a part of a video sequence, and at least one classification includes a video program type.

Abstract: Face detection apparatus generating an output indicative of the likelihood of test regions of a test image containing a face comprises: means for deriving a plurality of sets of image attribute data from the test region, each set relating to the test region scaled by a respective different scaling factor from a geometric progression of scaling factors, the progression being such that each scaling factor is related to a next scaling factor by a predetermined multiplicative factor, the factor being the same across the whole progression of scaling factors; means for comparing the derived attributes for each scaling factor with a first respective set of attributes indicative of the presence of a face to generate a first respective likelihood value; means for comparing the derived attributes for each scaling factor with a second respective set of attributes indicative of the presence of a face to generate a second respective likelihood value; means for generating a combined likelihood value in respect of at least

Abstract: A system and associated methodology of detecting objects using multiple sets of object probability data relating to different respective expected object sizes relative to the image size. A list of locations in an image where an object has been detected is stored, the list defining a probability data set and a probability value for each detected object. Object locations in a set of object probability data as locations at which a local maximum probability value exceeds a threshold probability value are detected and, if that location is substantially similar to a location previously stored in the list, where the local maximum probability value exceeds that relating to the previously stored location. The storing is repeated successively in respect of each set of probability data.

Abstract: Video face detection apparatus in which a test image from a video sequence is compared with an image property model derived from image properties of a region detected to contain a face in a preceding image in the video sequence comprises: selecting a predetermined proportion of pixels in the region detected to contain a face in the preceding image which most closely match the image property model derived in respect of that region, thereby deriving a pixel mask; and comparing pixels in the test image defined by the pixel mask with the image property model, the mask being applied at more than one image position within the test image; a face being detected in the test image at a mask position corresponding to a lowest average difference between the image property model and pixels defined by the mask at that position.

Abstract: A method of comparing a test image with a set of reference images. The method: divides the test image into one or more test regions; for each test region, compares the test region with one or more reference regions in one or more reference images and identifies the reference region that most closely corresponds to the test region; and generates a comparison value from the comparisons of the test regions with their correspondingly identified reference regions.

Abstract: Face detection apparatus in which an image region of a test image is compared with data indicative of the presence of a face comprises: a pre-processor operable to identify low-difference regions of the test image where there exists less than a threshold image difference across groups of pixels within those regions; and a face detector operable to perform face detection on regions of the test image other than those identified by the pre-processor as low-difference regions.

Abstract: A video camera arrangement comprises an image capture device; a face detector for detecting human faces in the captured video material and for generating face data identifying detected occurrences of faces in the captured video material; a data handling medium by which data representing the captured images is transmitted and/or stored; and a processor for generating data to be transmitted or stored by the data handling medium in dependence on the detection of faces in the captured images.

Abstract: A face detection apparatus for tracking a detected face between images in a video sequence comprises: a first face detector for detecting the presence of face(s) in the images; a second face detector for detecting the presence of face(s) in the images; the first face detector having a higher detection threshold than the second face detector, so that the second face detector is more likely to detect a face in an region in which the first face detector has not detected a face; and a face position predictor for predicting a face position in a next image in a test order of the video sequence on the basis of a detected face position in one or more previous images in the test order of the video sequence; in which: if the first face detector detects a face within a predetermined threshold image distance of the predicted face position, the face position predictor uses the detected position to produce a next position prediction; if the first face detector fails to detect a face within a predetermined threshold image d

Abstract: Face detection apparatus generating an output indicative of the likelihood of test regions of a test image containing a face comprises means operable to compare a test region with face data indicative of the presence of a face in such a way as to detect plural respective likelihood value indicative of the likelihood of the test region containing a face of a group of respective different face sizes; and control means, responsive to metadata associated with the image defining one of a set of predetermined classifications of the image, for modifying the group and/or the likelihood values in dependence upon a face size or range of face sizes appropriate to the classification of that image.

Abstract: Video data processing apparatus, the video data comprising a sequence of images comprises: an object tracker operable to detect the presence of one or more objects within an image and to track a detected object across successive images; an identity associator operable to associate an identity with an object tracked by the object tracker; a counter operable, for a first and second identity, to count the number of images within which a tracked object associated with the first identity and a tracked object associated with the second identity have both been detected; and a similarity detector operable to determine whether two tracked objects are similar in appearance; the identity associator being operable to change the identity associated with a first tracked object to the identity associated with a second tracked object if: (a) the similarity detector determines that the first and second tracked objects are similar in appearance and (b) the count corresponding to the identities associated with the first and sec

Abstract: An image processing method for selecting a subset of n (where n is two or more) images representative of a test set of images comprises the step of: detecting a degree of similarity between images in the test set of images, so that the subset of images comprises those n images having substantially the lowest similarity with other images in the set.

Abstract: A display arrangement comprises an image display device having a first camera directed towards positions adopted by users viewing the display; one or more further cameras directed towards other respective locations; a face detector for detecting human faces in images captured by the cameras; and means for detecting those faces which appear in images captured by both the first camera and at least one of the further cameras.

Abstract: A display arrangement comprises an image display device having two or more sets of images for display; a camera directed towards positions adopted by users viewing the display; a face detector for detecting human faces in images captured by the camera, the face detector being arranged to detect faces in at least two face categories; and means, responsive to the a frequency of detection of categories of faces by the face detector at one or more different periods, for selecting a set of images to be displayed on the image display device at that time of day.

Abstract: Object detection apparatus in which regions of a test image from an ordered series of images are compared with data indicative of the presence of an object, comprises a change detector operable to detect regions of the test image which are substantially unchanged with respect to a previous image in the series; and an object detector operable not to perform object detection on regions of the test image identified by the change detector as being substantially unchanged.

Abstract: A method of detecting objects using multiple sets of object probability data relating to different respective expected object sizes relative to the image size comprises the steps of: (a) storing a list of locations in an image where an object has been detected, the list defining a probability data set and a probability value for each detected object; (b) detecting object locations in a set of object probability data as locations at which a local maximum probability value exceeds a threshold probability value and, if that location is substantially similar to a location previously stored in the list, where the local maximum probability value exceeds that relating to the previously stored location; and (c) repeating step (b) successively in respect of each set of probability data.