Self-calibration method and device for structured light depth camera of smart phone

Abstract

A self-calibration method and device for a structured light depth camera of a smart phone, which is composed of an infrared laser speckle projector, an image receiving sensor, a self-calibration module, a depth calculation module, and a mobile phone application processing AP. Speckle pattern, set the feature block in the reference speckle image, collect the input speckle image through the image receiving sensor, and search for the optimal matching block corresponding to the feature block in the input speckle image through the similarity criterion, and obtain the feature block and Match the offset between the blocks. Once the relative change of the optical axis between the projector and the image sensor occurs, the offset will change accordingly. Find the optimal offset according to certain rules and reversely adjust the reference speckle image , so that the center of the input speckle image and the center of the reference speckle image can form a self-feedback adjustment closed-loop system, so that the input speckle image and the corrected reference speckle image can always find the optimal matching relationship.

Description

technical field [0001] The invention relates to the technical fields of smart phones, smart cameras, and depth perception, in particular to a self-calibration method and device for a structured light depth camera of a smart phone. Background technique [0002] Depth camera is a camera with depth detection function, which has a wide range of applications and development prospects in 3D information extraction, object recognition, classification, motion tracking, machine vision, human-computer interaction, 3D printing, virtual reality and other fields. Embedded applications of depth cameras on smartphones will also gradually become popular. [0003] The structured light depth camera is mainly composed of a laser coded pattern projector, an image receiving sensor and a depth perception computing module. It can use monocular structured light or binocular structured light to obtain more accurate depth information without being affected by ambient light. The perception algorithm a...

AI Technical Summary

Problems solved by technology

In the self-calibration process, the mobile phone application processing AP is used to set the size and number of feature blocks, match the search window range, and find the best offset. The entire depth-sensing self-calibration process can also be completed by software acceleration or a dedicated IP core. In order to solve the problem of the decrease of depth accuracy and the increase of noise caused by the change of the optical axis of the infrared laser speckle projector and the infrared receiving image sensor during the use of the structured light depth camera of the smartphone, and realize the real-time depth self-calibration of the smartphone, improve its robustness

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