(Slides, NO Video)

Abstract

I will present a variety of temporal models of video that we have been studying (and developing on) for analysis and synthesis of video. Forsynthesis of videos, we have been developing representations that support example-based re-synthesis and spatio-temporal re-targeting. These approaches build on graph-based methods and we present techniques for similarity metrics for video, segmentation in video, and merging of different video streams. I will showcase a series of examples of these approaches applied to generate new videos.

For analysis of videos, we have developed a series of representations to observe and model activities in videos. Building on low-level measures of movement and motion in videos, we have incorporated higher-level temporal generative models to represent and recognize observed activities. I will discuss the strengths of a variety of State-based, Markovian, Grammar-based and Network-based representations that we have employed for recognizing activities from video. I will also discuss approaches for unsupervised discovery and recognition of activities.

Time permitting, I will describe some new efforts that move towards understanding mobile imaging and video, and video authoring and video on the web, Within these I will discuss issues of collaborative imaging, collective authoring, ad-hoc sensor networks, and peer production with images and videos. Using these concepts, to focus the conversation, I will discuss how all of these issues are impacting the field Journalism and Reporting and how we have started on a new interdisciplinary research and education effort, we call Computational Journalism.

Irfan Essa
Georgia Institute of Technology
School of Interactive Computing, GVU and RIM Centers
April 21, 2009.

(see the video of this presentation)

Abstract

Our consumption of images (photography/video) continues to grow with the pervasiveness of computing (networking, mobile and media) technologies into our daily lives. Everyone now has a mobile camera, and digital image capture, processing, and sharing has become ubiquitous in our society. This has led to a significant impact on we want to (a) create novel scenes, (b) share our experiences with images, and (c) interact with  large amounts of images and videos from many sources. In this talk, I will start  with a brief overview of series of ongoing efforts in the analysis of images and videos for rendering novel scenes, interacting with images/videos and collaboratively authoring new content. I will describe some work on video-based rendering and synthesizing novel videos (and scenes) and highlight the technical contributions being made in areas of Computational Photography and Video.

Using these sets of efforts as a foundation I will showcase where things are headed in terms of user generated content, media sharing, annotation, and reuse with large scale networks. In essence, everybody is a content, producer, distributor, and consumer. I will describe some new efforts that move towards understanding mobile imaging and video, and also discuss issues of collaborative imaging, collective authoring, ad-hoc sensor networks, and peer production with images and videos.  Using these concepts I will discuss how all of these issues are impacting the field Journalism and Reporting and how we have started on a new interdisciplinary research and education effort, we call Computational Journalism.  The concept of Computational Journalism includes more than just imaging, and relates to media and information in general and is aimed at the study of how we remain informed in this connected world. I will outline this new field and relate it back to imaging, with examples from some of our recent work in this new area.

 
Abstract

Digital image capture, processing, and sharing has become pervasive in our society. This has had significant impact on how we create novel scenes, how we share our experiences, and how we interact with images and videos. In this talk, I will present an overview of series of ongoing efforts in the analysis of images and videos for rendering novel scenes. First I will discuss (in brief) our work on Video Textures, where repeating information is extracted to generate extended sequences of videos. I will also describe some our extensions to this approach that allows for controlled generation of animations of video sprites. We have developed various learning and optimization techniques that allow for video-based animations of photo-realistic characters. Using these sets of approaches as a foundation, then I will show how new images and videos can be generated. I will show examples of Photorealistic and Non-photorealistic Renderings of Scenes (Videos and Images) and how these methods support the media reuse culture, so common these days with user generated content.   I will then describe some of our new efforts that move towards understanding mobile imaging and video, and also discuss issues of collaborative imaging and authoring and ad-hoc sensor networks, and peer production with images and videos, leading to a new concepts of how computation has impacted journalism. Time permitting, I will also share some of our efforts on video annotation and how we have taken some of these new concepts of video analysis to classrooms.