Devices, systems, and methods for generating illumination-invariant images are disclosed. A method may include activating, by a device, a camera to capture first image data; while the camera is capturing the first image data, activating of a first, light source; receiving the first image data, the first image data having pixels having first color values; identifying first light generated by the first light source while the camera is capturing the first image data; identifying, based on the first image data, second light generated by a second light source; generating, based on the first light and the second light, second image data that are illumination-invariant; and presenting the second image data.

Example video processing systems and methods are described. In one implementation, compressed video data is received from a recording device. Additionally, metadata associated with the compressed video data is received such that the metadata includes frame-specific metadata associated with frames in the compressed video data. Further, an application program is received and configured to generate a real-time interactive experience for a user based on the compressed video data and the metadata associated with the compressed video data. A non-fungible token (NFT) is generated that includes the compressed video data, the metadata associated with the compressed video data, and the application program.

Systems and methods for providing a universal platform for at-home health testing and diagnostics are provided herein. In particular, a health testing and diagnostic platform is provided to connect medical providers with patients and to generate a unique, private testing environment. In some embodiments, the testing environment may facilitate administration of a medical test to a patient with the guidance of a proctor. In some embodiments, the patient may be provided with step-by-step instructions for test administration by the proctor within a testing environment. The platform may display unique, dynamic testing interfaces to the patient and proctor to ensure proper testing protocols and accurate test result verification.

An image processing system includes a processor, the processor performing processing, based on association information of an association between a biological image captured under a first imaging condition and a biological image captured under a second imaging condition, of outputting a prediction image corresponding to an image in which an object captured in an input image is to be captured under the second imaging condition. The association information is indicative of a trained model obtained through machine learning of a relationship between a first training image captured under the first imaging condition and a second training image captured under the second imaging condition. The processor is capable of outputting a plurality of different kinds of prediction images based on a plurality of trained models and the input image, and performs processing, based on a given condition, of selecting the prediction image to be output among a plurality of prediction images.

The invention concerns a method for converting an input image comprising an input luminance component made of elements into an output image comprising an output luminance component made of elements, the respective ranges of the output luminance component values and input luminance component element values being of different range extension. the method comprises for the input image: computing a value of a general variable representative of at least two input luminance component element values; transforming each input luminance component element value into a corresponding output luminance component element value according to the computed general variable value; and converting the input image using the determined output luminance component element values. The transforming step uses a set of pre-determined output values organized into a 2D Look-Up-Table (2D LUT) comprising two input arrays indexing a set of chosen input luminance component values and a set of chosen general variable values respectively, each pre-determined output value matching a pair of values made of an indexed input luminance component value and an indexed general variable value, the input luminance component element value being transformed into the output luminance component element value using at least one predetermined output value.

Methods and systems for providing a bitstream comprising video data encoded by an encoder apparatus are described, wherein the method may include: a processor of the encoder apparatus determining a current motion vector of a current block of a current video frame of a sequence of video frames comprising video data, the current motion vector defining a spatial offset of the current block relative to a prediction block of a previously encoded reference video frame stored in a memory of the encoder apparatus; the processor determining or receiving motion information associated with the current video frame, the motion information signaling the processor whether at least part of the offset defined by the current motion vector is associated with non-uniform motion in the video data of the current video frame; the processor determining a motion vector predictor candidate based on the motion information, at least a first motion vector predicator algorithm and a second motion vector predictor algorithm; and, the processor determining a motion vector difference based on the selected motion vector predictor candidate and the current motion vector; and, the processor using an encoding process to encode a residual block, the motion vector difference, an indication of the selected motion vector predictor candidate, and at least part of the motion information into a bitstream, wherein the residual block defines a difference between the current block and the prediction block.

An exemplary object masking system is configured to mask a recognized object during an application of a synthetic element to an original image. For example, the object masking system accesses a model of a recognized object depicted in an original image of a scene. The object masking system associates the model with the recognized object. The object masking system then generates presentation data for use by a presentation system to present an augmented version of the original image in which a synthetic element added to the original image is, based on the model as associated with the recognized object, prevented from occluding at least a portion of the recognized object. In this way, the synthetic element is made to appear as if located behind the recognized object. Corresponding systems and methods are also disclosed.

A spectral imaging system includes an objective lens system, an optical splitter, a dispersion system, and an optical combiner. The optical splitter is arranged to be in an optical path of an object being imaged through the objective lens system to provide an imaging optical path and a spectrometer optical path. The dispersion system is arranged in the spectrometer optical path. The optical combiner is arranged in the imaging optical path and a path of dispersed light from the dispersion system to combined dispersed light with a corresponding optical image of the object.

The present invention provides a loop closure detection method and system, a multi-sensor fusion SLAM system, a robot, and a medium. Said system runs on a mobile robot, and comprises a similarity detection unit, a visual pose solving unit, and a laser pose solving unit. According to the loop closure detection system, the multi-sensor fusion SLAM system and the robot provided in the present invention, the speed and accuracy of loop closure detection in cases of a change in a viewing angle of the robot, a change in the environmental brightness, a weak texture, etc. can be significantly improved.

An image frame loss detection method is performed by a computer device, including: acquiring first coded data respectively corresponding to a plurality of first image frames and a color signal corresponding to at least one second image frame; obtaining second coded data corresponding to at least one second image frame generated by a terminal device through image rendering of a color signal based on the coded data respectively corresponding to the plurality of first image frames; and comparing the first coded data respectively corresponding to the plurality of first image frames with the second coded data corresponding to the at least one second image frame to determine whether a frame loss occurs. The first coded data and the second coded data each include color-coded data respectively corresponding to M image blocks of a correspond image frame, and each of the M image blocks has a color in the image frame.