A Robotic Framework for Video Recording and Authoring
Jun Kato

Masataka Goto

National Institute of Advanced Industrial Science and Technology (AIST), Japan{jun.kato, m.goto}@aist.go.jp

ABSTRACTAuthoring videos that demonstrate interactive applications withhuman-computer and human-robot interactions are not easy. It
typically involves many retakes, each of which requires repetitive
actions in the authoring tools. To address the issue, we propose a
robotic framework that covers not only the camera but also therecording environment. It allows the user to annotate the video
when being recorded to eliminate tedious post-processing. This
demonstration shows an example recording setup consisted of arobot or tablet device (interactive applications) and the proposed
robotic camera system. The attendees can examine the framework
through video authoring experience with the system.

Keywords

Robotic camera system, video authoring, toolkit.

1. INTRODUCTION

Recording, editing, and sharing videos that demonstrate humancomputer and human-robot interactions (HCI, HRI) have becomecommon not only for the research community but also for theindustry to appeal the products and for end-users to share theirexperience with the interactive applications. However, authoringhigh-quality videos is still time-consuming and not easy. There
have been proposed robotic camera systems that follow aesthetic
guidelines for taking photos [1] and recognize the scene to control
the camera for framing interesting subjects [2]. Meanwhile, priorwork has mostly focused on the recording process, and the overall
difficulty remains. It comes from potentially a lot of retakes andthe resulting repetitive operations in the video authoring tools toapply appropriate editing effects [3].
To eliminate the tedious post-processing, DemoCut [4] provides a
dedicated user interface for annotating the recorded video. Thesystem then automatically edits the video with appropriate effects.
Our work shares its goal but focuses on adding annotations during(not after) the recording process. To achieve this, we extend therobotic camera approach to augment not only the camera itself but
also the recording environment. In this one-page abstract, we
briefly explain the proposed framework and discuss its potential.

2. PROPOSED ROBOTIC FRAMEWORKOur robotic framework helps to author videos of interactive
applications by adding annotations during the recording process.
The annotations can be categorized into a) session management,b) camera control, and c) overlaying information. These can bemade in two ways after the user starts recording. One way is toshow our predefined markers to the camera (e.g. “add a new

Figure 1. Overview of the proposed robotic camera system.
session” or “discard the ongoing session,” Figure 1a). Thesemarkers are recognized by the camera server with the ARToolkit.
The other way is to embed a small program developed with ourtoolkit in the interactive applications (Figure 1b). The toolkit
provides APIs that tell the camera to manage sessions, look at a
specific direction, and show or hide captions. In the current
system, the toolkit supports JavaScript and Java applications andconnects to the camera server through the Socket.io library.
Once the user is satisfied and stops recording, the camera serveredits the video following the annotations, producing video clips
with captions for each session. Even when the user wants a retake,there is no need for tedious post-processing tasks.

3. DISCUSSION AND FUTURE WORKWe proposed a robotic framework for addressing repetitive postprocessing operations in the authoring process of demonstration
videos. The framework essentially adds time-coded metadata to
the recorded videos that are used to edit the video. The metadata
can be added instantly by the user, which eliminates the need tokeep in mind which session was success/failure. The meta-data
can be added programmatically, which eliminates the manual
operations to input captions at appropriate timings.
While our current implementation only allows showing static textbased captions on the videos, the future work could allow its
animation as shown in TextAlive [5] and allow a robot application
to stream its first-person view to be presented as picture-in-picture
video. The video and timeline interface help to understand theinternal state of physical interactive applications. We foresee that
our framework can also be used for debugging robot applications.

4. REFERENCES[1] Gadde, R., et al. Aesthetic Guideline Driven Photography byRobots. In Proc. of IJCAI '11. 2060-2065.
[2] Pixio. 2011. Move ‘N See – Your Personal Robot
Cameraman. http://www.movensee.com.
[3] Muller, E. 2009. Where Quality Matters: Discourses on theArt of Making a YouTube Video. The YouTube Reader. 126-139.
[4] Chi, P., et al. DemoCut. In Proc. of UIST '13. 141-150.
[5] Kato, J., et al. TextAlive. In Proc. of CHI '15. 3403-3412.