Figure 1: In this paper, we present a novel high-resolution video stitching framework for real-time VR. We adapt image resolution and levelof-detail by estimating foveal region. The yellow circle indicates a highly-salient region thus rendered in high resolution, while red circle indicates less important region thus rendered in low resolution. The proposed foveated stitching greatly reduces the number of pixels to be processed and overall graphics computation. AbstractIn virtual reality (VR) applications, the contents are usually generated by creating a 360 • video panorama of a real-world scene. Although many capture devices are being released, getting high-resolution panoramas and displaying a virtual world in realtime remains challenging due to its computationally demanding nature. In this paper, we propose a real-time 360 • video foveated stitching framework, that renders the entire scene in different level of detail, aiming to create a high-resolution panoramic video in real-time that can be streamed directly to the client. Our foveated stitching algorithm takes videos from multiple cameras as input, combined with measurements of human visual attention (i.e. the acuity map and the saliency map), can greatly reduce the number of pixels to be processed. We further parallelize the algorithm using GPU to achieve a responsive interface and validate our results via a user study. Our system accelerates graphics computation by a factor of 6 on a Google Cardboard display.
In recent years, personalized fabrication has received considerable attention because of the widespread use of consumer‐level three‐dimensional (3D) printers. However, such 3D printers have drawbacks, such as long production time and limited output size, which hinder large‐scale rapid‐prototyping. In this paper, for the time‐ and cost‐effective fabrication of large‐scale objects, we propose a hybrid 3D fabrication method that combines 3D printing and the Zometool construction set, which is a compact, sturdy and reusable structure for infill fabrication. The proposed method significantly reduces fabrication cost and time by printing only thin 3D outer shells. In addition, we design an optimization framework to generate both a Zometol structure and printed surface partitions by optimizing several criteria, including printability, material cost and Zometool structure complexity. Moreover, we demonstrate the effectiveness of the proposed method by fabricating various large‐scale 3D models.
In recent years, personalized fabrication has received considerable attention because of the widespread use of consumer-level three-dimensional (3D) printers. However, such 3D printers have drawbacks, such as long production time and limited output size, which hinder large-scale rapid-prototyping. In this paper, for the time-and cost-effective fabrication of large-scale objects, we propose a hybrid 3D fabrication method that combines 3D printing and the Zometool construction set, which is a compact, sturdy, and reusable structure for infill fabrication. The proposed method significantly reduces fabrication cost and time by printing only thin 3D outer shells. In addition, we design an optimization framework to generate both a Zometool structure and printed surface partitions by optimizing several criteria, including printability, material cost, and Zometool structure complexity. Moreover, we demonstrate the effectiveness of the proposed method by fabricating various large-scale 3D models.
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