30 results about "Colored graph" patented technology

The invention discloses a method for constructing a depth image super-resolution reconstruction network based on color image guidance. At present, more and more scene applications require high-quality and high-resolution depth images. Traditional depth image super-resolution methods are not as effective and fast as convolutional neural network-based methods, but most super-resolution convolutional neural network frameworks They all just stack single-size convolution kernels, which cannot extract favorable guiding information from high-resolution color images in the same scene. The multi-scale convolution kernel color image guidance network of the present invention can not only fully explore the high-resolution color image information, extract useful feature images, but also enrich the diversity of depth image features, and fuse these information to perform super-resolution on depth images rate reconstruction. And the idea of ​​recursive learning and residual learning is used to reduce the burden of the convolutional neural network, control the parameters of the network, and improve the reconstruction effect of the depth image.

The invention discloses a method for setting random comparison verification code in an Internet webpage login system. According to the method, when a user logs in the system, a server side logging in the system generates a set of verification data and a set of comparison tables by a generation algorithm of an operation container module in an encryption graph form according to user information and reflects the data and the tables on a login interface, and in this way, the user can obtain the final verification code by referring to the comparison tables according to the verification data, input the verification code into the system and log in the system successfully. According to the method, colored graphs of English letters or Chinese characters corresponding to a set of 10 random numbers are provided for the numbers of the verification code, clear comparison table texts are beneficial for reading and selection of the user, the security of the verification code is improved, and moreover, the user can read and input the verification code conveniently.

The invention discloses a color map guide-based depth map restoration and view synthesis optimization method, which comprises the following steps: firstly, detecting inconsistent regions, detecting the edge of an input depth map, performing swelling processing on the edge, and marking the swelled edge as a potential inconsistent region; secondly, constructing a weight based on an iterative reweighting-based least squares algorithm, and after weight construction is completed, performing integral solving, and updating a depth map; judging whether the iteration is performed for set times or not according to a result; and if YES, outputting the depth map, and ending the calculation, or redetecting the inconsistent regions. The color map guide-based depth map restoration and view synthesis optimization method disclosed by the invention can suppress strong noise and restore inconsistent regions between the depth map and a color map to improve the consistency between the depth map and the color map and restore a correct boundary of the depth map, and has important guiding significance for improving the quality of a synthesized view. Meanwhile, the denoising and edge retaining capacity forconsistent regions is high; and an adopted matured iterative weighted least squares model is high in adaptability to parameters, and the robustness of the model is improved.

The embodiment of the invention discloses a three-dimensional measurement method and system. Based on a principle of color step phase encoding stripe auxiliary color trapezoid phase shift stripe decoding, a triangle principle is employed to achieve that two color patterns are employed to complete three-dimensional measurement so as to effectively reduce the number of projection patterns, reduce the calculated amount and speed up the processing speed, and the three-dimensional measurement method and system are not sensitive to the camera noise and the ambient light, is high in anti-jamming capability and improves the measurement precision.

The present application relates to an image super-resolution and coloring method, system and electronic equipment. The method includes: step a: design a new network model in combination with image super-resolution and coloring, and the network model includes an encoding module and a decoding module; step b: input the low-resolution grayscale image into the network model; step c: pass the The encoding module extracts the semantic feature map of the low-resolution grayscale image, and passes the semantic feature map to the decoding module, and the decoding module superimposes the semantic feature maps of each level and outputs a high-resolution color map. This application designs a new network model for super-resolution and coloring problems, and jointly processes super-resolution and coloring tasks, directly maps low-resolution grayscale images to high-resolution color images, improves people's visual perception, and saves resources and time.

The present invention provides a depth camera positioning method based on a convolutional neural network, comprising the following steps: establishing a convolutional neural network, the convolutional neural network includes a graph fusion generation module and a graph neural network module, and the graph fusion generation module It is used to jointly encode the color image obtained by the depth camera and the depth image to generate an interconnected fusion image, and the graph neural network module is used to process the fusion image; the convolutional neural network is trained based on an offline sample set, and the The above offline sample set includes batch images taken by the depth camera in the area to be located and the camera position when each frame of image is taken; when positioning is required, use the depth camera to take a set of color images and depth images in the area to be located as input , outputting the position of the camera for capturing the set of image data through the convolutional neural network. Through the method of the present invention, the color image acquired by the depth camera and the depth image can be fused and input to calculate the camera pose.

The invention discloses a method and device for implementing interactive image segmentation and a terminal. The method comprises the following steps: acquiring a color map, a depth map, and a mask map that marks the foreground point and the background point of the map; determining the first segmentation parameters of respective pixels in the mask map according to the color map and the mask map, determining the second segmentation parameters of respective pixels in the mask map according to the depth map and the mask map, and fusing the two types of segmentation parameters; constructing a undirected graph, mapping the fused segmentation parameter of each pixel in the mask map into the undirected graph, processing the undirected graph according to a min-cut / max-flow algorithm to obtain a finely-segmented mask map, and segmenting an image corresponding to the foreground point in the finely-segmented mask map from the color map. The method and device can improve an image segmentation effect in combination with the depth information of the image.