Abstract: Systems and methods permit generation of a digital scan of a user's face such as for obtaining of a patient respiratory mask, or component(s) thereof, based on the digital scan. The method may include: receiving video data comprising a plurality of video frames of the user's face taken from a plurality of angles relative to the user's face, generating a three-dimensional representation of a surface of the user's face based on the plurality of video frames, receiving scale estimation data associated with the received video data, the scale estimation data indicative of a relative size of the user's face, and scaling the digital three-dimensional representation of the user's face based on the scale estimation data. In some aspects, the scale estimation data may be derived from motion information collected by the same device that collects the scan of the user's face.

Abstract: Systems and methods permit generation of a digital scan of a user's face such as for obtaining of a patient respiratory mask, or component(s) thereof, based on the digital scan. The method may include: receiving video data comprising a plurality of video frames of the user's face taken from a plurality of angles relative to the user's face, generating a three-dimensional representation of a surface of the user's face based on the plurality of video frames, receiving scale estimation data associated with the received video data, the scale estimation data indicative of a relative size of the user's face, and scaling the digital three-dimensional representation of the user's face based on the scale estimation data. In some aspects, the scale estimation data may be derived from motion information collected by the same device that collects the scan of the user's face.

Abstract: Systems and methods permit generation of a digital scan of a user's face such as for obtaining of a patient respiratory mask, or component(s) thereof, based on the digital scan. The method may include: receiving video data comprising a plurality of video frames of the user's face taken from a plurality of angles relative to the user's face, generating a three-dimensional representation of a surface of the user's face based on the plurality of video frames, receiving scale estimation data associated with the received video data, the scale estimation data indicative of a relative size of the user's face, and scaling the digital three-dimensional representation of the user's face based on the scale estimation data. In some aspects, the scale estimation data may be derived from motion information collected by the same device that collects the scan of the user's face.

Abstract: Systems and methods permit generation of a digital scan of a user's face such as for obtaining of a patient respiratory mask, or component(s) thereof, based on the digital scan. The method may include: receiving video data comprising a plurality of video frames of the user's face taken from a plurality of angles relative to the user's face, generating a three-dimensional representation of a surface of the user's face based on the plurality of video frames, receiving scale estimation data associated with the received video data, the scale estimation data indicative of a relative size of the user's face, and scaling the digital three-dimensional representation of the user's face based on the scale estimation data. In some aspects, the scale estimation data may be derived from motion information collected by the same device that collects the scan of the user's face.

Abstract: Systems and methods permit generation of a digital scan of a user's face such as for obtaining of a patient respiratory mask, or component(s) thereof, based on the digital scan. The method may include: receiving video data comprising a plurality of video frames of the user's face taken from a plurality of angles relative to the user's face, generating a three-dimensional representation of a surface of the user's face based on the plurality of video frames, receiving scale estimation data associated with the received video data, the scale estimation data indicative of a relative size of the user's face, and scaling the digital three-dimensional representation of the user's face based on the scale estimation data. In some aspects, the scale estimation data may be derived from motion information collected by the same device that collects the scan of the user's face.

Abstract: A computer-implemented method (400) to generate an avatar, such as an avatar forming part of synthetic user generated content. The method comprises determining a rigid model based on an appearance error, a shape error and a dimensionality (425) of received images (405), and an appearance component and shape component of the rigid model. The non-rigid digital model may be a person specific active appearance model. Other aspects of include a computer system (200) and software (225).

Abstract: The invention relates to detecting and tracking objects in a sequence of images. In particular, a method, software and system for tracking a non-rigid object in a plurality of images. Initially, a first set of parameters for a parameterized shape model are generated (410) based on a first image. Then a second set of parameters are generated (415) for the parameterized shape model by fitting the parameterized shape model to the object in a second image of the plurality of images. This fitting is according to (i) the one or more constraints defined independently of the object or (ii) the first set of parameters. Also, the first and second sets of parameters define a tracking of the non-rigid object between the first and second images.

Abstract: Systems and methods permit generation of a digital scan of a user's face such as for obtaining of a patient respiratory mask, or component(s) thereof, based on the digital scan. The method may include: receiving video data comprising a plurality of video frames of the user's face taken from a plurality of angles relative to the user's face, generating a three-dimensional representation of a surface of the user's face based on the plurality of video frames, receiving scale estimation data associated with the received video data, the scale estimation data indicative of a relative size of the user's face, and scaling the digital three-dimensional representation of the user's face based on the scale estimation data. In some aspects, the scale estimation data may be derived from motion information collected by the same device that collects the scan of the user's face.

Abstract: The invention relates to detecting and tracking objects in a sequence of images. In particular, a method, software and system for tracking a non-rigid object in a plurality of images. Initially, a first set of parameters for a parameterised shape model are generated (410) based on a first image. Then a second set of parameters are generated (415) for the parameterised shape model by fitting the parameterised shape model to the object in a second image of the plurality of images. This fitting is according to (i) the one or more constraints defined independently of the object or (ii) the first set of parameters. Also, the first and second sets of parameters define a tracking of the non-rigid object between the first and second images.

Abstract: A scale estimating method through metric reconstruction of objects using a smart device is disclosed, in which the smart device is equipped with a camera for image capture and an inertial measurement unit (IMU). The scale estimating method is adapting a batch, vision-centric approach only using IMU to estimate the metric scale of a scene reconstructed by algorithm with Structure from Motion like (SfM) output. Monocular vision and noisy IMU can be integrated with the disclosed scale estimating method, in which a 3D structure of an object of interest up to an ambiguity in scale and reference frame can be resolved. Gravity data and a real-time heuristic algorithm for determining sufficiency of video data collection are utilized for improving upon scale estimation accuracy so as to be independent of device and operating system. Application of the scale estimation includes determining pupil distance and 3D reconstruction using video images.

Abstract: A scale estimating method through metric reconstruction of objects using a smart device is disclosed, in which the smart device is equipped with a camera for image capture and an inertial measurement unit (IMU). The scale estimating method is adapting a batch, vision-centric approach only using IMU to estimate the metric scale of a scene reconstructed by algorithm with Structure from Motion like (SfM) output. Monocular vision and noisy IMU can be integrated with the disclosed scale estimating method, in which a 3D structure of an object of interest up to an ambiguity in scale and reference frame can be resolved. Gravity data and a real-time heuristic algorithm for determining sufficiency of video data collection are utilized for improving upon scale estimation accuracy so as to be independent of device and operating system. Application of the scale estimation includes determining pupil distance and 3D reconstruction using video images.

Abstract: A computer-implemented method (400) to generate an avatar, such as an avatar forming part of synthetic user generated content. The method comprises determining a rigid model based on an appearance error, a shape error and a dimensionality (425) of received images (405), and an appearance component and shape component of the rigid model. The non-rigid digital model may be a person specific active appearance model. Other aspects of include a computer system (200) and software (225).