Tsinghua University

Tsinghua Shenzhen International Graduate School

Guolin Li

Zhihua Wang

Xiang Xie

Songping Mai

Wei Song

Yi Zheng

Zhong Lv

Lifei Ren

Jiawen Xue

Yiqiao Liao

Shaofeng Zou

A implicit structured light decoding method, a computer equipment and a computer-readable storage medium. The method includes: traversing an image captured by a camera to acquire a grayscale value of each pixel point and an ideal neighborhood grayscale distribution; extracting and outputting an updated output image according to the grayscale value of each pixel point and the ideal neighborhood grayscale distribution and in combination with a preset output image; classifying stripe central points in the updated output image into different stripes; determining a correspondence between stripes in the updated output image and stripes in a structured light image according to the different stripes; and decoding all stripe central points by using triangulation method in combination with the correspondence between the extracted stripes and the projected stripe pattern. This solution can efficiently and robustly decode the implicit stripe-based structured light on a basis of ensuring precision.

Implicit structured light decoding method, computer equipment and readable storage medium

A video blind denoising method based on deep learning, a computer device and a computer-readable storage medium. The method includes: taking a video sequence from a video to be denoised, taking the middle frame in the video sequence as a noisy reference frame, performing an optical flow estimation on the image corresponding to the noisy reference frame and each other frame in the video sequence, to obtain optical flow fields; transforming, according to the optical flow fields, the image corresponding to each other frame in the video sequence to the noisy reference frame for registration respectively, to obtain multi-frame noisy registration images; taking the multi-frame noisy registration images as an input of a convolutional neural network, taking the noisy reference frame as the reference image, performing iterative training and denoising by using the noise2noise training principle, to obtain the denoised image. This solution may achieve the blind denoising of a video.

Video blind denoising method based on deep learning, computer equipment and storage medium

The present invention relates to the technical field of the human computer interaction, more particularly to, a system and method for human computer interaction. The system for human computer interaction comprises a projection unit, a first image sensing unit, a second image sensing unit, an interface unit, an image processing unit, a projected interface processing unit, and a controlling unit. The system for human computer interaction provided by the present invention may easily project the human computer interaction interface on all kinds of planes encountered in people's daily life, to realize display of the human computer interaction interface everywhere, and improve users' experience.

System and method for human computer interaction

Growing community of inventors

Beijing, China

Guolin Li