Ryohei Funakoshi
Hideki Koike
ABSTRACT
We present a video stabilization algorithm for ball camera systems that undergo extreme egomotion during sports play. In particular, we focus on the BallCam system which is an American football embedded with an action camera at the tip of the ball. We propose an activity-aware video stabilization algorithm which is able to understand the current activity of the BallCam, which uses estimated activity labels to inform a robust video stabilization algorithm. Activity recognition is performed with a deep convolutional neural network, which uses optical flow.
Supplemental Material
- Kitani, K., Horita, K., Koike, H.: Ballcam!: dynamic view synthesis from spinning cameras. In: Adjunct proceedings of the 25th annual ACM symposium on User interface software and technology, ACM (2012) Google Scholar
Digital Library
- Poleg, Y., Ephrat, A., Peleg, S., Arora, C.: Compact cnn for indexing egocentric videos. In: WACV. (2016)Google Scholar
- Grundmann, M., Kwatra, V., Essa, I.: Auto-directed video stabilization with robust l1 optimal camera paths. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). (2011) Google ScholarDigital Library
- Farnebäck, G.: Two-frame motion estimation based on polynomial expansion. In: Image analysis. Springer (2003) 363--370 Google ScholarDigital Library
Index Terms
- Activity-Aware Video Stabilization for BallCam
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