Efficient hierarchical graph-based video segmentation
Georgia Institute of Technology · Google (United States)
Abstract
We present an efficient and scalable technique for spatiotemporal segmentation of long video sequences using a hierarchical graph-based algorithm. We begin by over-segmenting a volumetric video graph into space-time regions grouped by appearance. We then construct a “region graph” over the obtained segmentation and iteratively repeat this process over multiple levels to create a tree of spatio-temporal segmentations. This hierarchical approach generates high quality segmentations, which are temporally coherent with stable region boundaries, and allows subsequent applications to choose from varying levels of granularity. We further improve segmentation quality by using dense optical flow to guide temporal…
Citation impact
- FWCI
- 36.16
- Percentile
- 100%
- References
- 28
Authors
4Topics & keywords
- Computer science
- Segmentation
- Image segmentation
- Artificial intelligence
- Graph
- Computer vision
- Theoretical computer science