• DOI:10.1007/978-3-319-30208-9_13
• Corpus ID: 45423782

Understanding Uncertainty Issues in the Exploration of Fish Counts

@inproceedings{BeauxisAussalet2016UnderstandingUI,
  title={Understanding Uncertainty Issues in the Exploration of Fish Counts},
  author={Emma Beauxis-Aussalet and Lynda Hardman},
  booktitle={Fish4Knowledge},
  year={2016}
}

• Emma Beauxis-Aussalet, L. Hardman
• Published in Fish4Knowledge 2016
• Computer Science

Several data analysis steps are required for understanding computer vision results and drawing conclusions about the actual trends in the fish populations. Particular attention must be drawn to the potential errors that can impact the scientific validity of end-results. This chapter discusses the means for ecologists to investigate the uncertainty in computer vision results. We address a set of uncertainty factors identified by interviewing both ecology and computer vision experts, as discussed in Chap. 2. We investigate state-of-the-art methods to specify these uncertainty factors. We identify issues with conveying the results of ground-truth evaluation methods to end-users who are not familiar with computer vision technology, and we present a novel visualization design addressing these issues. Finally, we discuss the uncertainty factors for which evaluation methods require further research.