Live video object tracking and segmentation using graph cuts

Zachary Garrett, Hideo Saito

研究成果: Conference contribution

8 引用 (Scopus)

抜粋

Graph cuts have proven to be powerful tools in image segmentation. Previous graph cut research has proposed methods for cutting across large graphs constructed from multiple layered video frames, resulting in an object being tracked across multiple frames. However, this research focuses on cutting graphs constructed from a prerecorded video sequence. In live video scenarios, frames cannot be layered to construct 3D volumes, since the contents of the subsequent frames are unknown. Instead, new graphs must be created and cut for each frame on demand. Resource limitations make this unfeasible on high-resolution videos. In addition, object tracking requires a method for incorporating the previous frame's object position and shape into the current graph. We propose a method for tracking and segmenting objects in live video that utilizes regional graph cuts and object pixel probability maps. The regionalization of the cuts around the tracked object will increase the speed of the tracker, and the object pixel probability maps will enable more flexible tracking.

元の言語English
ホスト出版物のタイトル2008 IEEE International Conference on Image Processing, ICIP 2008 Proceedings
ページ1576-1579
ページ数4
DOI
出版物ステータスPublished - 2008 12 1
イベント2008 IEEE International Conference on Image Processing, ICIP 2008 - San Diego, CA, United States
継続期間: 2008 10 122008 10 15

出版物シリーズ

名前Proceedings - International Conference on Image Processing, ICIP
ISSN(印刷物)1522-4880

Other

Other2008 IEEE International Conference on Image Processing, ICIP 2008
United States
San Diego, CA
期間08/10/1208/10/15

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

フィンガープリント Live video object tracking and segmentation using graph cuts' の研究トピックを掘り下げます。これらはともに一意のフィンガープリントを構成します。

  • これを引用

    Garrett, Z., & Saito, H. (2008). Live video object tracking and segmentation using graph cuts. : 2008 IEEE International Conference on Image Processing, ICIP 2008 Proceedings (pp. 1576-1579). [4712070] (Proceedings - International Conference on Image Processing, ICIP). https://doi.org/10.1109/ICIP.2008.4712070