2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Login Paper Search My Schedule Paper Index Help

My ICIP 2021 Schedule

Note: Your custom schedule will not be saved unless you create a new account or login to an existing account.
  1. Create a login based on your email (takes less than one minute)
  2. Perform 'Paper Search'
  3. Select papers that you desire to save in your personalized schedule
  4. Click on 'My Schedule' to see the current list of selected papers
  5. Click on 'Printable Version' to create a separate window suitable for printing (the header and menu will appear, but will not actually print)

Paper Detail

Paper IDARS-4.8
Paper Title MULTI-CAMERA VIDEO SCENE GRAPHS FOR SURVEILLANCE VIDEOS INDEXING AND RETRIEVAL
Authors Toshal Patel, Alvin Yan Hong Yao, National University of Singapore, Singapore; Yu Qiang, Seagate Technology, Singapore; Wei Tsang Ooi, Roger Zimmermann, National University of Singapore, Singapore
SessionARS-4: Re-Identification and Retrieval
LocationArea I
Session Time:Wednesday, 22 September, 08:00 - 09:30
Presentation Time:Wednesday, 22 September, 08:00 - 09:30
Presentation Poster
Topic Image and Video Analysis, Synthesis, and Retrieval: Image & Video Storage and Retrieval
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Modern video surveillance systems often consist of multiple cameras capturing continuous videos. However, existing systems do not fully take advantage of shared scene semantics across multiple video streams, and hence querying the captured videos to find an event or object of interest can be a time-consuming task. In this paper, we propose a compact representation of objects and their relationships in the scene under surveillance, over time, and across multiple cameras, using a combined global spatio-temporal scene graph. The same objects that appear in multiple cameras are stored only once, reducing the storage required and speeding up the query when compared to storing the scene graph from each camera individually. Our experiments show that in a 5-camera system our proposed representation can speed up querying time by a factor of 3.9 times.