A method and apparatus for detecting a liveness based on a phase difference are provided. The method includes generating a first phase image based on first visual information of a first phase, generating a second phase image based on second visual information of a second phase, generating a minimum map based on a disparity between the first phase image and the second phase image, and detecting a liveness based on the minimum map.

Methods and systems for developing a sizing system through categorization and selection of prototypes, which can be regarded as the most appropriate fit model, is described. Once categorized and prototypes are selected, recommendations for the sizing of a target body part may be issued.

Systems and methods analyze a data set including a plurality of images. In one implementation, at least one processor receives a plurality of images acquired by one or more cameras associated with at least one vehicle; and analyzes the plurality of images using an active learning system configured to determine a relative priority ranking among the plurality of images. The relative priority ranking indicates an ordered sequence for the plurality of images, and is determined based on at least one indicator, determined for each of the plurality of images, of a complexity level and a diversity level associated with representations of one or more objects represented in the plurality of images. The at least one processor then outputs information indicating the relative priority ranking among the plurality of images.

A sensor calibration system configured to receive a first frame of one or more markers on a repositionable platform at a first location within a space from a sensor. The system is further configured to determine pixel locations in the first frame for a first marker and a second marker from among the one or more markers. The system is further configured to receive distance information that corresponds with a distance between the platform and distance measuring devices. The system is further configured to determine (x,y) coordinates for the first marker and the second marker based on the distance information. The system is further configured to generate a homography based on the (x,y) coordinates and pixel locations of the first marker and the second marker. The homography includes coefficients that translate between pixel locations in the first frame of the sensor and (x,y) coordinates in the global plane.

A sensor calibration system configured to receive a first frame of one or more markers on a repositionable platform at a first location within a space from a sensor. The system is further configured to determine pixel locations in the first frame for a first marker and a second marker from among the one or more markers. The system is further configured to receive distance information that corresponds with a distance between the platform and distance measuring devices. The system is further configured to determine (x,y) coordinates for the first marker and the second marker based on the distance information. The system is further configured to generate a homography based on the (x,y) coordinates and pixel locations of the first marker and the second marker. The homography includes coefficients that translate between pixel locations in the first frame of the sensor and (x,y) coordinates in the global plane.

A method includes obtaining, using at least one processor of an electronic device, multiple calibration parameters associated with multiple sensors of a selected mobile device. The method also includes obtaining, using the at least one processor, an identification of multiple imaging tasks. The method further includes obtaining, using the at least one processor, multiple synthetically-generated scene images. In addition, the method includes generating, using the at least one processor, multiple training images and corresponding meta information based on the calibration parameters, the identification of the imaging tasks, and the scene images. The training images and corresponding meta information are generated concurrently, different ones of the training images correspond to different ones of the sensors, and different pieces of the meta information correspond to different ones of the imaging tasks.

The present disclosure relates to a gesture recognition apparatus. The gesture recognition apparatus may include a gesture processor and a plurality of depth cameras connecting to the gesture processor. Each of the plurality of the depth cameras may include a controller and a collector. The controller may be configured to generate and transmit an acquisition signal to the collector in response to a trigger signal. The collector may be configured to receive the acquisition signal and perform an image acquisition process in response to the acquisition signal.

An imaging apparatus includes: a wiring board; an imaging unit that includes a lens module and an imaging element mounted on the wiring board; a housing that assumes a frame shape and includes an opening in the direction of an optical axis of the imaging unit; a top cover placed over the housing; a light source that emits light to travel to the outside through the top cover; and a light guide body that surrounds the lens module and guides the light emitted from the light source, wherein the imaging unit is spaced apart from the top cover by a space, the housing includes a bulging section bulging toward the lens module without being in contact the wiring board, and the bulging section receives a load applied from the top cover via at least the light guide body.

A method and system for generating a three-dimensional representation of a vehicle to assess damage to the vehicle. A mobile device may capture multispectral scans of a vehicle from each a plurality of cameras configured to scan the vehicle at a different wavelength of the electromagnetic spectrum. A virtual model of the vehicle may be generated from the multispectral scan of the vehicle, such that anomalous conditions or errors in individual wavelength data are omitted from model generation. A representation of the virtual model may be presented to the user via the display of the mobile device. The virtual model of the vehicle may further be analyzed to assess damage to the vehicle.

Provided herein are a calibration method for a fingerprint sensor and a display device using the calibration method, where, in the calibration method for a fingerprint sensor, the fingerprint sensor includes a substrate, a light-blocking layer located on a first surface of the substrate and having openings formed in a light-blocking mask, a light-emitting element layer located on the light-blocking layer and having a plurality of light-emitting elements, and a sensor layer located on a second surface of the substrate and having a plurality of photosensors; and the calibration method includes generating calibration data through white calibration and dark calibration, and applying offsets to the plurality of photosensors using the calibration data.