Abstract: The present disclosure generally pertains to time-of-flight data generation circuitry, configured to: acquire a time-of-flight (ToF) data stream using a ToF camera; acquire a brightness change event data stream using an event-based vision sensor (EVS), camera; correlate the time-of-flight data stream with the brightness change event data stream in time with each other for generating at least one time-of-flight data frame; and generate the at least one time-of-flight data frame based on the correlation.

Abstract: A configuration control circuitry for a time-of-flight system, the time-of-flight system including an illumination source configured to emit light to a scene and an image sensor configured to generate image data representing a time-of-flight measurement of light reflected from the scene.

Abstract: An electronic device comprising circuitry configured to unwrap a depth map or phase image by an artificial intelligence algorithm to obtain an unwrapped depth map is disclosed. A main input is subject to denoising to obtain a pre-processed main input, such as a pre-processed depth map. An artificial intelligence process, e.g. a convolutional neural network such as CNN has been trained to determine wrapping indexes from main input and side information data. This artificial intelligence process is performed on the pre-processed main input and pre-processed side information to obtain respective wrapping indexes. A postprocessing, such as an unwrapping algorithm is performed based on the wrapping indexes to obtain an unwrapped depth map. The U-Net architecture is used in a specific type of segmentation task, in which the boundaries are not dictated by objects but by passing unambiguous range boundaries.

Abstract: The present disclosure generally pertains to a time-of-flight sensing circuitry for sensing image information in different imaging modes, having: a light sensing circuitry for detecting light and outputting light sensing signals; and a logic circuitry for processing the light sensing signals from the light sensing circuitry, wherein the logic circuitry is configured to decide an imaging mode among the different imaging modes.

Abstract: The present disclosure pertains to an analysis portion for a time-of-flight imaging portion, wherein the time-of-flight imaging portion includes at least one imaging element of a first type and at least one imaging element of a second type, wherein the at least one imaging element of the first type and the at least one imaging element of the second type are arranged in a predetermined pattern, configured to: construct first imaging data of the at least one imaging element of the first type based on second imaging element data of the at least one imaging element of the second type, wherein the first imaging data are constructed based on a machine learning algorithm.