Kinect is a motion sensing input device which is widely used in computer vision and other related fields. However, there are many inaccurate depth data in Kinect depth images even Kinect v2. In this paper, an algorithm is proposed to enhance Kinect v2 depth images. According to the principle of its depth measuring, the foreground and the background are considered separately. As to the background, the holes are filled according to the depth data in the neighborhood. And as to the foreground, a filling algorithm, based on the color image concerning about both space and color information, is proposed. An adaptive joint bilateral filtering method is used to reduce noise. Experimental results show that the processed depth images have clean background and clear edges. The results are better than ones of traditional Strategies. It can be applied in 3D reconstruction fields to pretreat depth image in real time and obtain accurate results.
The study was to investigate the influence on stereoscopic cognition with different densities and dot sizes of static random-dot stereograms (RDS). The responses of every subject were recorded with different densities of RDS (10%, 20%, 30%, 40%) and different dot sizes of RDS (2*2 pix, 3*3 pix, 4*4 pix). The results showed that reaction times decreased with increasing densities of RDS and dot sizes of RDS. The reaction time was the shortest when the density of RDS was 30%. And when the dot size was 4*4 pix, the mean response time was the shortest. Therefore, when the density of RDS was 30% and the dot size of RDS was 4*4 pix, it was the most convenient for the stereoscopic cognition.
Visualization of water surface is a hot topic in computer graphics. In this paper, we presented a fast method to generate wide range of water surface with good image quality both near and far from the viewpoint. This method utilized uniform mesh and Fractal Perlin noise to model water surface. Mipmapping technology was enforced to the surface textures, which adjust the resolution with respect to the distance from the viewpoint and reduce the computing cost. Lighting effect was computed based on shadow mapping technology, Snell’s law and Fresnel term. The render pipeline utilizes a CPU-GPU shared memory structure, which improves the rendering efficiency. Experiment results show that our approach visualizes water surface with good image quality at real-time frame rates performance.
Shadow mapping is commonly used in real-time rendering. In this paper, we presented an accurate and efficient method of soft shadows generation from planar area lights. First this method generated a depth map from light’s view, and analyzed the depth-discontinuities areas as well as shadow boundaries. Then these areas were described as binary values in the texture map called binary light-visibility map, and a parallel convolution filtering algorithm based on GPU was enforced to smooth out the boundaries with a box filter. Experiments show that our algorithm is an effective shadow map based method that produces perceptually accurate soft shadows in real time with more details of shadow boundaries compared with the previous works.
We introduce an algorithm for real-time sub-pixel accurate hard shadows rendering. The method focuses on addressing the shadow aliasing due to the limited resolution of shadow maps. We store a partial, approximate geometric representation of the scene’s surfaces which are visible to the light source. Inspired by the fact that aliasing occurs in the shadow silhouette regions, we present an edge detection algorithm using second-order Newton’s Divide Difference to divide shadow maps into two regions: depth-discontinuous region and depth-continuous region. A tangent estimation method based on the geometry shadow map is presented to recover the artifact aliasing of those silhouette regions. Experiments show that our algorithm eliminates the resolution issues and generates hard shadows with high quality.