Abstract: Provided is a posture recognition system that can properly respond to an error that is changed according to a user's motion. A posture estimation section calculates posture data indicating a posture of a user wearing clothing, on the basis of motion data measured by a posture sensor attached to the clothing. An error estimation section calculates error data which is an estimate of an error that is occurring in the posture data, on the basis of the motion data and the posture data.

Abstract: A camera (1) for monitoring a monitored area (2), including a camera sensor (4) for generating at least one unmasked surveillance image (6) of the monitored area (2) and/or of a subarea of the monitored area (2), the camera sensor (4) being configured for providing raw data, the raw data encompassing the at least one unmasked surveillance image (6), and including an integrated evaluation unit (5), the evaluation unit (5) encompassing an input interface (8) for receiving the raw data and encompassing an output interface (17) for providing output image data.

Abstract: A camera (1) for monitoring a monitored area (2), including a camera sensor (4) for generating at least one unmasked surveillance image (6) of the monitored area (2) and/or of a subarea of the monitored area (2), the camera sensor (4) being configured for providing raw data, the raw data encompassing the at least one unmasked surveillance image (6), and including an integrated evaluation unit (5), the evaluation unit (5) encompassing an input interface (8) for receiving the raw data and encompassing an output interface (17) for providing output image data.

Abstract: A method and system of identifying in an image captured by a second camera a target object captured by a first camera is disclosed. The method comprises using image captured by the 1st camera for generating a first set of objects comprising the target object and other objects; classifying each object to generate a reference group of attribute values characterizing the objects; using image captured by the 2nd camera for generating second sets of objects; classifying each object in each second set to generate, for each second set, a corresponding group of attribute values characterizing the objects in the corresponding second set; selecting the second set of objects corresponding to the group of attribute values best matching the reference group of attribute values; and identifying the target object in the selected second set of objects in accordance with a position of the target object in the first set of objects.

Abstract: A method, system and computer program product for detecting an object within a frame, the method comprising: receiving calibration parameters of a camera; obtaining four or more salient points of an object model, wherein a plane containing the salient points is at an arbitrary position relatively to a frame view of the camera; determining a projection of each of the at least four salient feature points onto the frame view of the camera, thus determining a quadrilateral in frame coordinates; determining a transformation for transforming the quadrilateral into a rectangle having edges parallel to edges of frames captured by the camera; receiving at least a part of the frame captured by the camera; applying the transformation to the at least part of the frame to obtain a rectangular search area having edges parallel to edges of the frame; and detecting an object within the rectangular search area.

Abstract: A method and system of identifying in an image captured by a second camera a target object captured by a first camera is disclosed. The method comprises using image captured by the 1st camera for generating a first set of objects comprising the target object and other objects; classifying each object to generate a reference group of attribute values characterizing the objects; using image captured by the 2nd camera for generating second sets of objects; classifying each object in each second set to generate, for each second set, a corresponding group of attribute values characterizing the objects in the corresponding second set; selecting the second set of objects corresponding to the group of attribute values best matching the reference group of attribute values; and identifying the target object in the selected second set of objects in accordance with a position of the target object in the first set of objects.

Abstract: A target object captured by a first camera is identified in images captured by a second camera. A reference platoon comprising the target object and other objects is generated using first camera images. A reference group characterizing the objects in the reference platoon is generated by running a first set of trained classifiers over the reference platoon, the first set of trained classifiers trained to characterize objects captured by the first camera. Candidate platoons are generated using second camera images. Candidate groups characterizing objects in the candidate platoons are obtained by running an independently trained second set of classifiers over the candidate platoons, the second set characterizing objects captured by the second camera. Candidate groups are compared to the reference group, and a best matching candidate platoon is selected. The target object is identified in the selected candidate platoon based on the object's position in the reference platoon.

Abstract: Apparatus and method for extracting a background model from a video stream of frames. Each frame is divided into a rectangular array of blocks, and a block descriptor of each block is compared with the previous frame's corresponding block descriptor. When a block descriptor is substantially the same as the corresponding block descriptor of the preceding frame for at least a predetermined number of frames, then the background model is updated according to the block descriptor.

Abstract: The invention provides methods and systems for reliably detecting objects in a received video stream from a camera. Objects are selected and a bound around selected objects is calculated and displayed. Bounded objects can be tracked. Bounding is performed by using Histogram of Oriented Gradients and linear Support Vector Machine classifiers.

Abstract: The invention extends to a tracking device for tracking a position of a moving object such as a human head or eyes, the device comprising a camera, a radiation source radiating electro-magnetic radiation, and a processor for calculating variables indicative of the position of an object relative to the camera, wherein the camera is adapted to capture images using illumination provided by the radiation source, wherein the radiation source comprises a source of infrared radiation and the camera comprises a monocular image input. Further aspects of the invention relate to an associated method for tracking a moving object; to quickly sorting a set of competing models of the users head; the use of threshold conversion to distinguish characteristics of captured images, and controlling the output of a three dimensional display in dependence on the tracked position of a user's head.

Abstract: The invention relates to a system for determining the position of a user and/or a moving device by means of tracking methods, in particular for augmented reality applications, with an interface (9) to integrate at least one sensor type and/or data generator (1, 2, 3, 4) of a tracking method, a configuration unit (20) to describe communication between the tracking methods and/or tracking algorithms and at least one processing unit (5, 6, 7, 8, 10, 11, 12, 13, 16) to calculate the position of the user and/or the moving device based on the data supplied by the tracking methods and/or tracking algorithms.

Abstract: The invention relates to a system for determining the position of a user and/or a moving device by means of tracking methods, in particular for augmented reality applications, with an interface (9) to integrate at least one sensor type and/or data generator (1, 2, 3, 4) of a tracking method, a configuration unit (20) to describe communication between the tracking methods and/or tracking algorithms and at least one processing unit (5, 6, 7, 8, 10, 11, 12, 13, 16) to calculate the position of the user and/or the moving device based on the data supplied by the tracking methods and/or tracking algorithms.