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Hsing-Ying Zhong

dblp:42/6128 · DBLP profile ↗
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5ranked-venue papers
0as first author
0since 2021 · last 2009
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 5Artificial intelligence and machine learning · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
4 papers
Visual content generation and editing · 57% Image and video processing · 43%
Artificial intelligence
1 paper
Video understanding and tracking · 100%

Topics — the 6 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visual content generation and editing
video editing
0.222009
Motion inpainting and extrapolation for special effect production · ACM Multimedia 2009
Video falsifying by motion interpolation and inpainting · CVPR 2008
Image and video processing › video restoration
video inpainting
0.222008
Motion extrapolation for video story planning · ACM Multimedia 2008
Video falsifying by motion interpolation and inpainting · CVPR 2008
Image and video processing › video restoration
motion inpainting
0.112009
Motion inpainting and extrapolation for special effect production · ACM Multimedia 2009
Visual content generation and editing
video generation
0.112008
Motion extrapolation for video story planning · ACM Multimedia 2008
Visual content generation and editing › texture synthesis
dynamic texture synthesis
0.012009
Motion inpainting and extrapolation for special effect production · ACM Multimedia 2009
Image and video processing
motion analysis
0.012008
Motion extrapolation for video story planning · ACM Multimedia 2008

Methods — techniques the papers use, named apart from their topics

motion interpolation · 0.2graph cuts · 0.2motion inpainting · 0.1frame interpolation · 0.1video inpainting · 0.1video combination · 0.1video alteration · 0.1motion tracking · 0.1motion extrapolation · 0.1mean-shift tracking · 0.1mean shift tracking · 0.1
YearPublicationVenuePosition
2009 Motion inpainting and extrapolation for special effect production
abstract
Special effect production is an important technology for movie industry. Although sophisticated equipments can be used to produce scenery such as fire and smoke, usually, the approach is expensive and perhaps dangerous. Can sceneries be re-produced based on existing videos using digital technology? The answer is yes but it is difficult. In this video demonstration, we propose new mechanisms using motion inpainting technologies. Dynamic texture can be altered and reused under control. In addition, actors with repeated motion can be interpolated or extrapolated and incorporated into the falsified scenery. We demonstrate using our tool to produce realistic video narratives based on existing videos. Five sets of results as well as the source videos used are available at http://member.mine.tku.edu.tw/www/ACMMM09VideoDemo.
Nick C. Tang, Hsing-Ying Zhong, Joseph C. Tsai, Timothy K. Shih, Hong-Yuan Mark Liao
ACM Multimedia2
2008 Video falsifying by motion interpolation and inpainting
abstract
We change the behavior of actors in a video. For instance, the outcome of a 100-meter race in the Olympic game can be falsified. We track objects and segment motions using a modified mean shift mechanism. The resulting video layers can be played in different speeds and at different reference points with respect to the original video. In order to obtain a smooth movement of target objects, a motion interpolation mechanism is proposed based on continuous stick figures (i.e., a video of human skeleton) and video inpainting. The video inpainting mechanism is performed in a quasi-3D space via guided 3D patch matching for filling. Interpolated target objects and background layers are fused by using graph cut. It is hard to tell whether a falsified video is the original. We demonstrate the original and the falsified videos in our website at http://www.mine.tku.edu.tw/video_demo/). The proposed technique can be used to create special effects in movie industry.
Timothy K. Shih, Nick C. Tang, Joseph C. Tsai, Hsing-Ying Zhong
CVPR4
2008 Motion extrapolation for video story planning
abstract
We create video scenes using existing videos. A panorama is generated from background video, with foreground objects removed by video inpainting technique. A video planning script is provided by the user on the panorama with accurate timing of actors. Actions of these actors are extensions of existing cyclic motions, such as walking, tracked and extrapolated using our motion analysis techniques. Although the types of video story generated are limited, however, it is possible to use the mechanism proposed to generate forgery videos. Interested readers should visit our tool demonstration and forgery videos at http://member.mine.tku.edu.tw/www/ACMMM08-VideoPlanning.
Nick C. Tang, Timothy K. Shih, Hong-Yuan Mark Liao, Joseph C. Tsai, Hsing-Ying Zhong
ACM Multimedia5
2008 Video falsifying for special effect production
abstract
Video Falsifying is a technique for generating fake video by altering, combining, or creating new video contents. For instance, the outcome of a 100-meter race can be changed. Alternatively, the winner of a horse race can be created from combined videos. The technique is for special effect production in movie industry. We demonstrate how to use our video falsifying techniques in special effects production. Interested readers should look at our demonstration website at http://member.mine.tku.edu.tw/www/ACMMM08VideoDemo.
Nick C. Tang, Timothy K. Shih, Hsing-Ying Zhong, Joseph C. Tsai, Chin-Yao Tang
ACM Multimedia3
2007 Scratch Line Removal on Aged Films
abstract
Aged motion pictures may contain different types of defects, such as spikes and scratch lines. Several detection mechanisms were proposed to find scratches. However, it is relatively hard to precisely restore aged films if the continuation of image property is not considered in the temporal domain. This paper proposes a technique on restoring aged films based on simultaneously considering the outmost patches/pixels which are going to be inpainted. The inpainting order plays an important factor for human visualization. By eliminating the inpainting order problem, the results of restored films have good quality as compared to earlier approach. Application of our technique can be used in the restoration of aged films.
Yang-Ta Kao, Timothy K. Shih, Hsing-Ying Zhong, Liang-Kuang Dai
ISM3