Demo Data from SIGIR 2026 / reviewers in the wild / expert
Shengqiu Huang
dblp:224/0682
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 2
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 |
Computer animation and physical simulation · 100% | |
| Theoretical computer science
1 paper |
Mathematical optimization · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer animation and physical simulation › virtual cinematography
camera motion planning |
0.3 | 1 | 2018 | Creating and chaining camera moves for quadrotor videography · ACM Trans. Graph. 2018 |
Computer animation and physical simulation
trajectory optimization |
0.3 | 1 | 2018 | Creating and chaining camera moves for quadrotor videography · ACM Trans. Graph. 2018 |
Mathematical optimization
combinatorial optimization |
0.1 | 1 | 2018 | Creating and chaining camera moves for quadrotor videography · ACM Trans. Graph. 2018 |
Mathematical optimization › combinatorial optimization › vehicle routing
traveling salesman problem |
0.1 | 1 | 2018 | Creating and chaining camera moves for quadrotor videography · ACM Trans. Graph. 2018 |
Methods — techniques the papers use, named apart from their topics
view quality field · 0.7set traveling salesman problem · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Uncut Aerial Video via a Single SketchabstractAbstract Nowadays UAV filming is getting popular, more and more stunning aerial videos appearing online. Nonetheless, making a good uncut aerial video with only one‐long‐shot for the large‐scale outdoor scenes is still quite challenging, no many eye‐catching pieces available yet. It requires users to have both consummate drone controlling skill and good perception of filming aesthetics. If totally manual, the user has to simultaneously adjust the drone position and the mounted camera orientation during the whole flyby while trying to keep all operation changes executed smoothly. Recent research has proposed a number of planning tools for automatic or semi‐automatic aerial videography, however, most requires rather complex user inputs and heavy computations. In this paper, we propose a user‐friendly system designed to simplify the input and automatically generate continuous camera moves to capture compelling aerial videos that users prefer to see without any post cutting or editing. Assume a rough 2.5D scene model that includes all the regions of interest are available, users are only required to casually draw a single sketch on the 2D map. Our system will analyze this rough sketch input, compute the corresponding quality views in 3D safe flying zone, and then create a globally optimal camera trajectory passing through regions of user interest via solving a combinatorial problem. At end, we optimize the drone flying speed locally to make the resulting aerial videos more visually pleasing. Ke Xie 0001, Shengqiu Huang, Hui Huang 0004 |
Comput. Graph. Forum | 3 |
| 2018 | Creating and chaining camera moves for quadrotor videographyabstractCapturing aerial videos with a quadrotor-mounted camera is a challenging creative task, as it requires the simultaneous control of the quadrotor's motion and the mounted camera's orientation. Letting the drone follow a pre-planned trajectory is a much more appealing option, and recent research has proposed a number of tools designed to automate the generation of feasible camera motion plans; however, these tools typically require the user to specify and edit the camera path, for example by providing a complete and ordered sequence of key viewpoints. In this paper, we propose a higher level tool designed to enable even novice users to easily capture compelling aerial videos of large-scale outdoor scenes. Using a coarse 2.5D model of a scene, the user is only expected to specify starting and ending viewpoints and designate a set of landmarks, with or without a particular order. Our system automatically generates a diverse set of candidate local camera moves for observing each landmark, which are collision-free, smooth, and adapted to the shape of the landmark. These moves are guided by a landmark-centric view quality field, which combines visual interest and frame composition. An optimal global camera trajectory is then constructed that chains together a sequence of local camera moves, by choosing one move for each landmark and connecting them with suitable transition trajectories. This task is formulated and solved as an instance of the Set Traveling Salesman Problem. Ke Xie 0001, Shengqiu Huang, Dani Lischinski, Marc Christie, Kai Xu 0004, Minglun Gong, Daniel Cohen-Or, Hui Huang 0004 |
ACM Trans. Graph. | 3 |