In this paper, we present a three-dimensional dissipative particle dynamics simulation, which is independent of the initial conditions, for analyzing the wettability on liquid-solid interfaces. The model parameters are constructed based on simulation optimization. The contact angle of a droplet on the solid platforms which possess different surface energy is simulated. The normalized factors indicate the parameters of the surface energy. By tuning the attractive and repulsive effects between the platform and the droplet, the contact angles with wide range are found at steady states. In simulation result, the linear relation between contact angle and the normalized factor is obtained.The proper repulsive factor in the paper is recommended to be 15 or 20. The ranges of the contact angles are from about 65 to 155 degrees. Moreover, the local density and the equation of state are applied for determining the droplet's self energy and compressibility. The simulation results will help us to predict the profile and internal physical behavior of a micro-droplet.
Fall prevention is an important issue particularly for the elderly. This paper proposes a camera-based line-laser obstacle detection system to prevent falls in the indoor environment. When obstacles are detected, the system will emit alarm messages to catch the attention of the user. Because the elderly spend a lot of their time at home, the proposed line-laser obstacle detection system is designed mainly for indoor applications. Our obstacle detection system casts a laser line, which passes through a horizontal plane and has a specific height to the ground. A camera, whose optical axis has a specific inclined angle to the plane, will observe the laser pattern to obtain the potential obstacles. Based on this configuration, the distance between the obstacles and the system can be further determined by a perspective transformation called homography. After conducting the experiments, critical parameters of the algorithms can be determined, and the detected obstacles can be classified into different levels of danger, causing the system to send different alarm messages.
This study proposes an automatic three-dimensional (3D) color shape measurement system based on images recorded by a stereo camera. The system, comprising several off-the-shelf components, is cost-effective yet capable of obtaining quality color 3D objects. In the proposed system, a turntable carrying a checkerboard is used to assist the simultaneous calibration of the stereo camera and the turntable. A slit laser is driven to swing forward and backward for generating stripes on test objects. The stereo images are collected and analyzed for obtaining matching pixels, and, consequently, the 3D point coordinates based on epipolar geometry are obtained. Screened Poisson reconstruction is utilized to integrate and smooth the scanned surfaces. With additional color images from the same camera, several multi-view texturing methods are benchmarked. We concluded that our proposed system can successfully and automatically reconstruct quality 3D color shapes of various objects.
A laser scan is useful in building the 3D model, and in one run it can capture thousands of 3D points. However these 3D points are sparse compared to a normal image, which can easily have millions of pixels. To achieve a denser 3D map, 3D-interpolation is applied to each pixel in the image.In this work we propose an algorithm to combine the 3D geometry and the color for 3D-interpolation. We segment the 3D points based on their latent surfaces, and combine the surfaces with color through Markov Random Field. We find that the 3D geometry provides rich information for interpolation: 3D points with similar colors can be robustly clustered where not possible in the color space, and the interpolation can be performed on a better fitting surface rather than on the locally linear ones. Our experiments show that the proposed algorithm outperforms the baselines.
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