Stories, Papers, WIKIs

Title Body
Using Graphics Processor Units (GPUs) for Automatic Video Structuring (IEEE)

Abstract

The rapid pace of development of graphic processor units (GPUs) in recent years in terms of performance and programmability has attracted the attention of those seeking to leverage alternative architectures for better performance than that which commodity CPUs can provide. In this paper, the potential of the GPU in automatically structuring video is examined, specifically in shot boundary detection and representative keyframe selection techniques. We first introduce the programming model of the GPU and outline the implementation of techniques for shot boundary detection and representative keyframe selection on both the CPU and GPU, using histogram comparisons. We compare the approaches and present performance results for both the CPU and GPU. Overall these results demonstrate the significant potential for the GPU in this domain.

Paper available at IEEE.

Real-time color holographic video display system (IEEE)

Abstract

A real-time multi-GPU color holographic video display system computes holograms from 3D video of a rigid object. System has three main stages; client, server and optics. 3D coordinate and texture information are kept in client and sent online to the server through the network. In the server stage, with the help of the parallel processing ability of the GPUs and segmentation algorithms, phase-holograms are computed in real-time. The graphic card of the server computer drives the SLMs and red, green and blue channels are controlled in parallel. Resultant color holographic video is loaded to the SLMs which are illuminated by expanded light from LEDs. In the optics stage, reconstructed color components are combined by using beam splitters. Reconstructions are captured by a CCD array without any supporting optics. Experimental results are satisfactory.

Paper available at IEEE.

H.264 video decoding compatible with Vector Graphics (IEEE)

Abstract

This work introduces a novel way to decode a video H.264 stream. An advanced Vector Graphics pipeline has been modified and used to decode H.264 Main Profile video bit streams, instead of using a native decoder. The Vector Graphics GPU can be used to perform tasks for which it was not originally intended: acceleration of video at resolutions between QCIF to Full HD without loss or any drift of quality compared to the H.264 native decoder output.

Paper available at IEEE.

GTC 2010: Working Man's Guide to 3D Video Editing - Ian Williams, Kevan O'Brien

Video editing is currently at two simultaneous inflections points: use of GPUs for video processing and the beginning of wide spread adoption of 3D. At this time however, identifying and navigating through the necessary tools and equipment to create compelling 3D video content is challenging. This session is intended to provide a pragmatic guide to creating prosumer 3D video content and how the GPU greatly assists and speeds up this process. The intended audience is anyone interested in how to create compelling 3D movies at a prosumer level.

GTC 2010: Working Man's Guide to 3D Video Editing - Ian Williams, Rudy Sarzo, Kevan O'Brien

Video editing is currently at two simultaneous inflections points: use of GPUs for video processing and the beginning of wide spread adoption of 3D. At this time however, identifying and navigating through the necessary tools and equipment to create compelling 3D video content is challenging. This session is intended to provide a pragmatic guide to creating prosumer 3D video content and how the GPU greatly assists and speeds up this process. The intended audience is anyone interested in how to create compelling 3D movies at a prosumer level.

GTC 2010: Developing GPU Enabled Visual Effects For Film And Video - Bruno Nicoletti

The arrival of fully programable GPUs is now changing the visual effects industry, which traditionally relied on CPU computation to create their spectacular imagery. Implementing the complex image processing algorithms used by VFX is a challenge, but the payoffs in terms of interactivity and throughput can be enormous. Hear how The Foundry's novel image processing architecture simplifies the implementation of GPU-enabled VFX software and eases the transition from a CPU based infrastructure to a GPU based one.

Video stabilization and motion deblurring on GPU (ACM)

As the video cameras used by amateur are relatively light and they are held by one hand, it is prone to be unstable. As a result the video sequences are affected by the vibrations of the video cameras and it is not comfortable to appreciate them.

Paper available at ACM.

GPU-accelerated hierarchical dense correspondence for real-time aerial video processing (ACM)

Video from aerial surveillance can provide a rich source of data for many applications and can be enhanced for display and analysis through such methods as mosaic construction, super-resolution, and mover detection. All of these methods require accurate frame-to-frame registration, which for live use must be performed in real time. In many situations, scene parallax may make alignment using global transformations impossible or error-prone, limiting the performance of subsequent processing and applications. For these cases, dense (per-pixel) correspondence is required, but this can be computationally prohibitive. This paper presents a hierarchical dense correspondence algorithm designed for implementation on graphics processing units (GPUs). Since the method does not rely on epipolar geometry, it is also suitable for use when there are uncorrected nonlinear lens distortions. A framework for using this dense correspondence to implement local mosaicking, super-resolution enhancement, and mover detection is also presented and demonstrated using examples of each of these types of enhancement and different types of video sources.

Paper available at ACM.

Exploring NVIDIA-CUDA for video coding (ACM)

Today, world is rapidly turning to high definition multimedia. From engineering and programming point of view, this usually means more computation is needed and more memory space is required to achieve these higher qualities. In this paper we explore the use of parallelization opportunities in graphics processors to accelerate video encoding. We evaluate the NVIDIA CUDA[1] toolkit and evaluate the performance of motion estimation in video encoding. The main goal of this paper is to evaluate the capabilities of NVIDIA/CUDA and develop a process for implementing video/multimedia applications. We have discovered that the difference in performance when CUDA is not used properly can be over 100x. We show how we were able to use CUDA capabilities to reduce the motion estimation time from 7000 milli seconds to 70 milli seconds.

Paper available at ACM.

Direct-to-indirect transfer for cinematic relighting (ACM)

This paper presents an interactive GPU-based system for cinematic relighting with multiple-bounce indirect illumination from a fixed view-point. We use a deep frame-buffer containing a set of view samples, whose indirect illumination is recomputed from the direct illumination on a large set of gather samples, distributed around the scene. This direct-to-indirect transfer is a linear transform which is particularly large, given the size of the view and gather sets. This makes it hard to precompute, store and multiply with. We address this problem by representing the transform as a set of sparse matrices encoded in wavelet space. A hierarchical construction is used to impose a wavelet basis on the unstructured gather cloud, and an image-based approach is used to map the sparse matrix computations to the GPU. We precompute the transfer matrices using a hierarchical algorithm and a variation of photon mapping in less than three hours on one processor. We achieve high-quality indirect illumination at 10-20 frames per second for complex scenes with over 2 million polygons, with diffuse and glossy materials, and arbitrary direct lighting models (expressed using shaders). We compute per-pixel indirect illumination without the need of irradiance caching or other subsampling techniques.

 

 

Paper available at ACM.