Human-assisted motion annotation
- 1 June 2008
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
Obtaining ground-truth motion for arbitrary, real-world video sequences is a challenging but important task for both algorithm evaluation and model design. Existing ground-truth databases are either synthetic, such as the Yosemite sequence, or limited to indoor, experimental setups, such as the database developed by Baker et al (2007). We propose a human-in-loop methodology to create a ground-truth motion database for the videos taken with ordinary cameras in both indoor and outdoor scenes, using the fact that human beings are experts at segmenting objects and inspecting the match between two frames. We designed an interactive computer vision system to allow a user to efficiently annotate motion. Our methodology is cross-validated by showing that human annotated motion is repeatable, consistent across annotators, and close to the ground truth obtained by Baker et al (2007). Using our system, we collected and annotated 10 indoor and outdoor real-world videos to form a ground-truth motion database. The source code, annotation tool and database is online for public evaluation and benchmarking.Keywords
This publication has 18 references indexed in Scilit:
- LabelMe: A Database and Web-Based Tool for Image AnnotationInternational Journal of Computer Vision, 2007
- On the Spatial Statistics of Optical FlowInternational Journal of Computer Vision, 2007
- Image Alignment and Stitching: A TutorialFoundations and Trends® in Computer Graphics and Vision, 2007
- Particle Video: Long-Range Motion Estimation using Point TrajectoriesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2006
- Video object cut and pastePublished by Association for Computing Machinery (ACM) ,2005
- Motion magnificationACM Transactions on Graphics, 2005
- A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statisticsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- An integrated Bayesian approach to layer extraction from image sequencesIeee Transactions On Pattern Analysis and Machine Intelligence, 2001
- CONDENSATION—Conditional Density Propagation for Visual TrackingInternational Journal of Computer Vision, 1998
- Fast surface interpolation using hierarchical basis functionsIeee Transactions On Pattern Analysis and Machine Intelligence, 1990