video signal processing

Summarization of user-generated sports video by using deep action recognition features

Automatically generating a summary of a sports video poses the challenge of detecting interesting moments, or highlights, of a game. Traditional sports video summarization methods leverage editing conventions of broadcast sports video that facilitate …

Textual description-based video summarization for video blogs

Recent popularization of camera devices, including action cams and smartphones, enables us to record videos in everyday life and share them through the Internet. Video blog is a recent approach for sharing videos, in which users enjoy expressing …

Free-viewpoint AR human-motion reenactment based on a single RGB-D video stream

When observing a person (an actor) performing or demonstrating some activity for the purpose of learning the action, it is best for the viewers to be present at the same time and place as the actor. Otherwise, a video must be recorded. However, …

Inferring what the videographer wanted to capture

Detecting important regions in videos has been extensively studied for past decades for their wide variety of applications including video summarization and retargeting. Visual attention models draw much attention for this purpose, which find …

Real-time privacy protection system for social videos using intentionally-captured persons detection

Most social videos, which are uploaded and shared through social networking services (SNSs), e.g., YouTube and Facebook, contain not only intentionally-captured persons (ICPs) but also non-ICPs who are unexpectedly framed in, such as passers-by. …

Markov random field-based real-time detection of intentionally-captured persons

Most videos taken by videographers contain intentionally-captured persons (ICPs), who are essential for what the videographers want to express in their video. This paper presents a method to detect ICPs in real-time. Whether a person in a video is an …

Discriminating intended human objects in consumer videos

In a consumer video, there are not only intended objects, which are intentionally captured by the camcorder user, but also unintended objects, which are accidentally framed-in. Since the intended objects are essential to present what the camcorder …