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Register a new userInteractive Sound Rendering on Mobile Devices using Ray-Parameterized Reverberation Filters
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Added by
Dinesh Manocha
Publication date
2018
fields
Informatics Engineering
and research's language is
English
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We present a new sound rendering pipeline that is able to generate plausible sound propagation effects for interactive dynamic scenes. Our approach combines ray-tracing-based sound propagation with reverberation filters using robust automatic reverb parameter estimation that is driven by impulse responses computed at a low sampling rate.We propose a unified spherical harmonic representation of directional sound in both the propagation and auralization modules and use this formulation to perform a constant number of convolution operations for any number of sound sources while rendering spatial audio. In comparison to previous geometric acoustic methods, we achieve a speedup of over an order of magnitude while delivering similar audio to high-quality convolution rendering algorithms. As a result, our approach is the first capable of rendering plausible dynamic sound propagation effects on commodity smartphones.
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We present a technique for rendering highly complex 3D scenes in real-time by generating uniformly distributed points on the scenes visible surfaces. The technique is applicable to a wide range of scene types, like scenes directly based on complex and detailed CAD data consisting of billions of polygons (in contrast to scenes handcrafted solely for visualization). This allows to visualize such scenes smoothly even in VR on a HMD with good image quality, while maintaining the necessary frame-rates. In contrast to other point based rendering methods, we place points in an approximated blue noise distribution only on visible surfaces and store them in a highly GPU efficient data structure, allowing to progressively refine the number of rendered points to maximize the image quality for a given target frame rate. Our evaluation shows that scenes consisting of a high amount of polygons can be rendered with interactive frame rates with good visual quality on standard hardware.
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In this paper, we present a learning-based method to the keyframe-based video stylization that allows an artist to propagate the style from a few selected keyframes to the rest of the sequence. Its key advantage is that the resulting stylization is semantically meaningful, i.e., specific parts of moving objects are stylized according to the artists intention. In contrast to previous style transfer techniques, our approach does not require any lengthy pre-training process nor a large training dataset. We demonstrate how to train an appearance translation network from scratch using only a few stylized exemplars while implicitly preserving temporal consistency. This leads to a video stylization framework that supports real-time inference, parallel processing, and random access to an arbitrary output frame. It can also merge the content from multiple keyframes without the need to perform an explicit blending operation. We demonstrate its practical utility in various interactive scenarios, where the user paints over a selected keyframe and sees her style transferred to an existing recorded sequence or a live video stream.
All mobile devices are energy-constrained. They use batteries that allows using the device for a limited amount of time. In general, energy attacks on mobile devices are denial of service (DoS) type of attacks. While previous studies have analyzed the energy attacks in servers, no existing work has analyzed the energy attacks on mobile devices. As such, in this paper, we present the first systematic study on how to exploit the energy attacks on smartphones. In particular, we explore energy attacks from the following aspect: hardware components, software resources, and network communications through the design and implementation of concrete malicious apps, and malicious web pages. We quantitatively show how quickly we can drain the battery through each individual attack, as well as their combinations. Finally, we believe energy exploit will be a practical attack vector and mobile users should be aware of this type of attacks.
The spatial anti-aliasing technique for line joins (intersections of the road segments) on vector maps is exclusively crucial to visual experience and system performance. Due to limitations of OpenGL API, one common practice to achieve the anti-aliased effect is splicing multiple triangles at varying scale levels to approximate the fan-shaped line joins. However, this approximation inevitably produces some unreality, and the system rendering performance is not optimal. To circumvent these drawbacks, in this paper, we propose a simple but efficient algorithm which uses only two triangles to substitute the multiple triangles approximation and then renders a realistic fan-shaped curve with alpha operation based on geometrical relation computing. Our experiment shows it has advantages of a realistic anti-aliasing effect, less memory cost, higher frame rate, and drawing line joins without overlapping rendering. Our proposed spatial anti-aliasing technique has been widely used in Internet Maps such as Tencent Mobile Maps and Tencent Automotive Maps.
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