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Pu-Sheng Hsu

dblp:131/0671 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 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
1 paper
Image and video processing · 50% Computational photography and imaging · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational photography and imaging › image stitching
parallax handling
0.212013
Spatially and Temporally Optimized Video Stabilization · IEEE Trans. Vis. Comput. Graph. 2013
Image and video processing
video stabilization
0.212013
Spatially and Temporally Optimized Video Stabilization · IEEE Trans. Vis. Comput. Graph. 2013

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

streaming · 0.2spatial-temporal optimization · 0.2bézier curve representation · 0.2
YearPublicationVenuePosition
2013 Spatially and Temporally Optimized Video Stabilization
abstract
Properly handling parallax is important for video stabilization. Existing methods that achieve the aim require either 3D reconstruction or long feature trajectories to enforce the subspace or epipolar geometry constraints. In this paper, we present a robust and efficient technique that works on general videos. It achieves high-quality camera motion on videos where 3D reconstruction is difficult or long feature trajectories are not available. We represent each trajectory as a Bézier curve and maintain the spatial relations between trajectories by preserving the original offsets of neighboring curves. Our technique formulates stabilization as a spatial-temporal optimization problem that finds smooth feature trajectories and avoids visual distortion. The Bézier representation enables strong smoothness of each feature trajectory and reduces the number of variables in the optimization problem. We also stabilize videos in a streaming fashion to achieve scalability. The experiments show that our technique achieves high-quality camera motion on a variety of challenging videos that are difficult for existing methods.
Yu-Shuen Wang, Feng Liu 0015, Pu-Sheng Hsu, Tong-Yee Lee
IEEE Trans. Vis. Comput. Graph.3