Video Frame Interpolation via Adaptive Separable Convolution

Standard video frame interpolation methods first estimate optical flow between input frames and then synthesize an intermediate frame guided by motion. Recent approaches merge these two steps into a single convolution process by convolving input frames with spatially adaptive kernels that account for motion and re-sampling simultaneously. These methods require large kernels to handle large motion, which limits the number of pixels whose kernels can be estimated at once due to the large memory demand. To address this problem, this paper formulates frame interpolation as local separable convolution over input frames using pairs of 1D kernels. Compared to regular 2D kernels, the 1D kernels require significantly fewer parameters to be estimated. Our method develops a deep fully convolutional neural network that takes two input frames and estimates pairs of 1D kernels for all pixels simultaneously. Since our method is able to estimate kernels and synthesizes the whole video frame at once, it allows for the incorporation of perceptual loss to train the neural network to produce visually pleasing frames. This deep neural network is trained end-to-end using widely available video data without any human annotation. Both qualitative and quantitative experiments show that our method provides a practical solution to high-quality video frame interpolation.Comment: ICCV 2017, http://graphics.cs.pdx.edu/project/sepconv

Evaluation of optimisation techniques for multiscopic rendering

A thesis submitted to the University of Bedfordshire in fulfilment of the requirements for the degree of Master of Science by ResearchThis project evaluates different performance optimisation techniques applied to stereoscopic and multiscopic rendering for interactive applications. The artefact features a robust plug-in package for the Unity game engine. The thesis provides background information for the performance optimisations, outlines all the findings, evaluates the optimisations and provides suggestions for future work. Scrum development methodology is used to develop the artefact and quantitative research methodology is used to evaluate the findings by measuring performance. This project concludes that the use of each performance optimisation has specific use case scenarios in which performance benefits. Foveated rendering provides greatest performance increase for both stereoscopic and multiscopic rendering but is also more computationally intensive as it requires an eye tracking solution. Dynamic resolution is very beneficial when overall frame rate smoothness is needed and frame drops are present. Depth optimisation is beneficial for vast open environments but can lead to decreased performance if used inappropriately

A Measurement Study of Live 360 Video Streaming Systems

360-degree live video streaming is becoming increasingly popular. While providing viewers with enriched experience, 360-degree live video streaming is challenging to achieve since it requires a significantly higher bandwidth and a powerful computation infrastructure. A deeper understanding of this emerging system would benefit both viewers and system designers. Although prior works have extensively studied regular video streaming and 360-degree video on demand streaming, we for the first time investigate the performance of 360-degree live video streaming. We conduct a systematic measurement of YouTube’s 360-degree live video streaming using various metrics in multiple practical settings. Our research insight will help to build a clear understanding of today’s 360-degree live video streaming and lay a foundation for future research on this emerging yet relatively unexplored area. To further understand the delay measured in YouTube’s 360-degree live video streaming, we conduct the second measurement study on a 360-degree live video streaming platform. While live 360-degree video streaming provides an enriched viewing experience, it is challenging to guarantee the user experience against the negative effects introduced by start-up delay, event-to-eye delay, and low frame rate. It is therefore imperative to understand how different computing tasks of a live 360-degree streaming system contribute to these three delay metrics. Our measurement provide insights for future research directions towards improving the user experience of live 360-degree video streaming. Based on our measurement results, we propose a motion-based trajectory transmission method for 360-degree video streaming. First, we design a testbed for 360-degree video playback. The testbed can collect the users viewing data in real time. Then we analyze the trajectories of the moving targets in the 360-degree videos. Specifically, we utilize optical flow algorithms and gaussian mixture model to pinpoint the trajectories. Then we choose the trajectories to be delivered based on the size of the moving targets. The experiment results indicates that our method can obviously reduce the bandwidth consumption

ObserVR

According to Superdata Digital Market Research, investors have poured more than $6 billion into the virtual reality market in the last three years, mostly to catalyze application development for virtual reality gaming. In the last decade, watching live streams of other gamers playing video games has skyrocketed, with the world’s largest esports streaming platform Twitch.tv receiving 53 million unique visitors daily. ObserVR intends to package these technologies and change the way users watch multiple 2D video streams in an immersive 3D environment. By accessing our service, a user can embed URLs for existing video streams through our online application and then launch a motion controlled multi-screen view within their virtual reality headset. By utilizing existing 2D content, our service is changing the current viewing experience by eliminating the hassle of manually changing web browser tabs and offering a way to become your own producer by choosing what camera angles you want to watch at any given time. By providing this service in three dimensions, we are able to bring benefits to each user that current technology does not allow. These benefits include saving time, decreasing hardware space, and providing a community base while enhancing current viewing methods. While most of the technology’s early adopters are gamers, virtual reality devices are expected to become the next household entertainment standard, meaning that the applications for this technology beyond gaming are boundless. To meet our customers’ needs, we will be building an online application that allows users to incorporate any available online video stream into our interface and create a customized viewing layout. Our initial interface will support up to four streams at any one time. By allowing users to embed and launch personally selected content, we are decreasing the amount of behavioral change needed for user adoption. We plan to include the ability to select content directly through our application dashboard, providing a library of all online streamable content

Providing 3D video services: the challenge from 2D to 3DTV quality of experience

Recently, three-dimensional (3D) video has decisively burst onto the entertainment industry scene, and has arrived in households even before the standardization process has been completed. 3D television (3DTV) adoption and deployment can be seen as a major leap in television history, similar to previous transitions from black and white (B&W) to color, from analog to digital television (TV), and from standard definition to high definition. In this paper, we analyze current 3D video technology trends in order to define a taxonomy of the availability and possible introduction of 3D-based services. We also propose an audiovisual network services architecture which provides a smooth transition from two-dimensional (2D) to 3DTV in an Internet Protocol (IP)-based scenario. Based on subjective assessment tests, we also analyze those factors which will influence the quality of experience in those 3D video services, focusing on effects of both coding and transmission errors. In addition, examples of the application of the architecture and results of assessment tests are provided

Augmented reality over maps

Dissertação de mestrado integrado em Engenharia InformáticaMaps and Geographic Information System (GIS) play a major role in modern society, particularly on tourism, navigation and personal guidance. However, providing geographical information of interest related to individual queries remains a strenuous task. The main constraints are (1) the several information scales available, (2) the large amount of information available on each scale, and (3) difficulty in directly infer a meaningful geographical context from text, pictures, or diagrams that are used by most user-aiding systems. To that extent, and to overcome the aforementioned difficulties, we develop a solution which allows the overlap of visual information over the maps being queried — a method commonly referred to as Augmented Reality (AR). With that in mind, the object of this dissertation is the research and implementation of a method for the delivery of visual cartographic information over physical (analogue) and digital two-dimensional (2D) maps utilizing AR. We review existing state-of-art solutions and outline their limitations across different use cases. Afterwards, we provide a generic modular solution for a multitude of real-life applications, to name a few: museums, fairs, expositions, and public street maps. During the development phase, we take into consideration the trade-off between speed and accuracy in order to develop an accurate and real-time solution. Finally, we demonstrate the feasibility of our methods with an application on a real use case based on a map of the city of Oporto, in Portugal.Mapas e Sistema de Informação Geográfica (GIS) desempenham um papel importante na sociedade, particularmente no turismo, navegação e orientação pessoal. No entanto, fornecer informações geográficas de interesse a consultas dos utilizadores é uma tarefa árdua. Os principais dificuldades são (1) as várias escalas de informações disponíveis, (2) a grande quantidade de informação disponível em cada escala e (3) dificuldade em inferir diretamente um contexto geográfico significativo a partir dos textos, figuras ou diagramas usados. Assim, e para superar as dificuldades mencionadas, desenvolvemos uma solução que permite a sobreposição de informações visuais sobre os mapas que estão a ser consultados - um método geralmente conhecido como Realidade Aumentada (AR). Neste sentido, o objetivo desta dissertação é a pesquisa e implementação de um método para a visualização de informações cartográficas sobre mapas 2D físicos (analógicos) e digitais utilizando AR. Em primeiro lugar, analisamos o estado da arte juntamente com as soluções existentes e também as suas limitações nas diversas utilizações possíveis. Posteriormente, fornecemos uma solução modular genérica para uma várias aplicações reais tais como: museus, feiras, exposições e mapas públicos de ruas. Durante a fase de desenvolvimento, tivemos em consideração o compromisso entre velocidade e precisão, a fim de desenvolver uma solução precisa que funciona em tempo real. Por fim, demonstramos a viabilidade de nossos métodos com uma aplicação num caso de uso real baseado num mapa da cidade do Porto (Portugal)