Visual Classification of Music Style Transfer Based on PSO-BP Rating Prediction Model

In this paper, based on computer reading and processing of music frequency, amplitude, timbre, image pixel, color filling, and so forth, a method of image style transfer guided by music feature data is implemented in real-time playback, using existing music files and image files, processing and trying to reconstruct the fluent relationship between the two in terms of auditory and visual, generating dynamic, musical sound visualization with real-time changes in the visualization. Although recommendation systems have been well developed in real applications, the limitations of CF algorithms are slowly coming to light as the number of people increases day by day, such as the data sparsity problem caused by the scarcity of rated items, the cold start problem caused by new items and new users. The work is dynamic, with real-time changes in music and sound. Taking portraits as an experimental case, but allowing users to customize the input of both music and image files, this new visualization can provide users with a personalized service of mass customization and generate personalized portraits according to personal preferences. At the same time, we take advantage of the BP neural network’s ability to handle complex nonlinear problems and construct a rating prediction model between the user and item attribute features, referred to as the PSO-BP rating prediction model, by combining the features of global optimization of particle swarm optimization algorithm, and make further improvements based on the traditional collaborative filtering algorithm.

A Numerical Method to Improve the Representativeness of Real Microstructure Cut-Outs Applied in Finite Element Simulations

To improve the representativeness of a real microstructural cut-out for modeling purposes, a numerical method named as “boundary pixel color alteration (BPCA)” is presented to modify measured 2D microstructure cut-outs. Its physical background is related to the phase growth. For the application, the precondition is that the representativeness of the microstructure is already satisfied to a certain extent. This method resolves the problem that the phase composition of a small cut-out can have a large discrepancy to the real one. The main idea is to change the pixel color among neighboring pixels belonging to different phases. Our process simultaneously maintains most of the characteristics of the original morphology and is applicable for nearly all kinds of multi-phase or polycrystalline metallic alloys, as well. From our axisymmetric finite element (FE) simulations (ABAQUS ) applied with 2D real microstructures, it shows that the volume ratios of microstructural phases, as a function of the structure position to the symmetric axis, converge to phase area ratios in the 2D cut-out, even though the axisymmetric element volume is position dependent. A mathematical proof provides the reason for the aforementioned convergence. As examples to achieve real compositions and to numerically prove the aforementioned convergence, four different materials including multiphase polycrystals are implemented. An improvement of the predicted FE result is presented for the application of a modified microstructure (with a higher representativeness) compared to the original one.

The mapping of raster images on plane isometric grid

Drawing images on curvilinear shapes with the least distortion takes place in many design tasks. In most ways, build a grid, each elementary cell of which is painted a given color. In this problem it is necessary to solve two main problems: the first - to carry out the formation of a given curvilinear grid with elementary cells in the form of squares, which are called isometric (or isothermal); the second is to paint each cell of the curved area with the corresponding pixel color of the original raster The aim of the study is to reveal the way of displaying raster images on flat curvilinear areas represented by isometric grids, and with the help of a computer model in the Maple symbolic algebra to analyze the influence of isometric grid parameters on the position and size of displayed raster images. The mapping of images onto curvilinear forms with minimal distortion takes place in many design tasks. A method of conformal mapping of arbitrary raster images onto plane curvilinear region is proposed, which are represented by isometric (also called isothermal) grids. The essence of the proposed method is as follows. Any raster image, for example, digital photography in jpg format, is characterized by the dimensions N×M - the number of pixels in width and height. In addition, each pixel has a color and brightness, which are arranged in rows and columns. To apply a raster image to a curvilinear region, it is also necessary to divide the curvilinear domain into N×M, the number of elementary squares, each of which is assigned the corresponding color from the raster. The influence and arguments of the various isometric grids constructed on the sizes and positions of an arbitrary raster image are investigated in the article. It is shown how the isometric grid, depending on and localizes the raster image - it can be located both within the limits of the isometric grid coordinate lines and beyond it, can also be oriented in different directions with respect to the and coordinate lines. It is shown the possibility of scaling a raster image that can be performed relative to the relative dimensions of an isometric grid. Since there is a correspondence between the pixel matrix of the original raster image and the - cells of the isometric grid, the rotation of the image will affect its position in the isometric grid. For example, rotating the original bitmap image at an angle 90 degrees will change its location on a plane isometric grids – from along the coordinate lines to along the coordinate lines. Note that, the curvilinear cells of the constructed isometric grids differ somewhat from the shape of the squares because the values and of the corresponding arguments and of their coordinate lines were taken somewhat too large. Otherwise, cells would degenerate into points and the corresponding grid image would not be so clear.

3-D Shape Reconstruction of Non-Uniform Reflectance Surface Based on Pixel Intensity, Pixel Color and Camera Exposure Time Adaptive Adjustment

Three-dimensional (3-D) surface reconstruction of reflective objects and colored objects is a challenge. To this end, we proposed a novel approach. First, a new method of pixel matching between the projected image and the captured image is proposed. Then, we analyzed the impact of color texture and reflective surface on the captured image quality, and proposed a black-and-white (B/W) camera-based color information extraction method, an object surface reflectance and ambient light interference estimation method. Finally, the pixel color, pixel intensity and exposure time can be adaptively adjusted according to the color information and reflectivity of the measured objects. Experiments verified that the proposed method can not only obtain high-quality captured images, but also has a smaller number of additional images and a wider range of applications than existing methods.

Object tracking algorithm by moving video camera

The algorithm ACT (Adaptive Color Tracker) to track objects by a moving video camera is presented. One of the features of the algorithm is the adaptation of the feature set of the tracked object to the background of the current frame. At each step, the algorithm extracts from the object features those that are more specific to the object and at the same time are at least specific to the current frame background, since the rest of the object features not only do not contribute to the separation of the tracked object from the background, but also impede its correct detection. The features of the object and background are formed based on the color representations of scenes. They can be computed in two ways. The first way is 3D-color vectors of the clustered image of the object and the background by a fast version of the well-known k-means algorithm. The second way consists in simpler and faster partitioning of the RGB-color space into 3D-parallelepipeds and subsequent replacement of the color of each pixel with the average value of all colors belonging to the same parallelepiped as the pixel color. Another specificity of the algorithm is its simplicity, which allows it to be used on small mobile computers, such as the Jetson TXT1 or TXT2.The algorithm was tested on video sequences captured by various camcorders, as well as by using the well-known TV77 data set, containing 77 different tagged video sequences. The tests have shown the efficiency of the algorithm. On the test images, its accuracy and speed overcome the characteristics of the trackers implemented in the computer vision library OpenCV 4.1.

Developing Augmented Reality Hybrid Marker using Pictorial Quick Response Code for Community Products

Applying augmented reality technology correctly helps businesses grow and attract more consumers, but using the marker that is the QR code does not directly interpret. On the other hand, if using pictorial markers, although they can convey meaning, it still takes time to process to extract the hidden information. This paper proposes to develop the hybrid marker for augmented reality by mixing the community brand image with the QR code for community product entrepreneurs, and develop the mobile application for scanning the hybrid marker then respond to the augmented reality content in several styles. The hybrid marker was generated into two modes. The opacity layer mode was set the opacity value of QR code to 55%. And overlapping mode is designed to invert the pixel color between pictorial band image and QR code. This system was evaluated in black-box testing. As a result, the efficiency of the hybrid marker and mobile application is the highest level of user acceptance while being used in this system.