# Visual Coin-Tracking: Tracking of Planar Double-Sided Objects

arXiv: https://arxiv.org/abs/1908.02664 · HTML: https://mlsanity.com/paper/1908.02664/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Aug 2019.

## Built on by (most cited first, 1 of 1)

- [Tracking by 3D Model Estimation of Unknown Objects in Videos](https://mlsanity.com/paper/2304.06419/) (2023)

## Abstract (arXiv)

We introduce a new video analysis problem -- tracking of rigid planar objects in sequences where both their sides are visible. Such coin-like objects often rotate fast with respect to an arbitrary axis producing unique challenges, such as fast incident light and aspect ratio change and rotational motion blur. Despite being common, neither tracking sequences containing coin-like objects nor suitable algorithm have been published. As a second contribution, we present a novel coin-tracking benchmark containing 17 video sequences annotated with object segmentation masks. Experiments show that the sequences differ significantly from the ones encountered in standard tracking datasets. We propose a baseline coin-tracking method based on convolutional neural network segmentation and explicit pose modeling. Its performance confirms that coin-tracking is an open and challenging problem.