Automatic Key Frame Extraction from Videos for Efficient Mouse Pain Scoring
Kopaczka M, Ernst L, Heckelmann J, Schorn C, Tolba R, Merhof D (2018)
Publication Type: Conference contribution
Publication year: 2018
Publisher: Institute of Electrical and Electronics Engineers Inc.
Pages Range: 248-252
Conference Proceedings Title: 2018 5th International Conference on Signal Processing and Integrated Networks, SPIN 2018
Event location: Noida, IND
ISBN: 9781538630457
DOI: 10.1109/SPIN.2018.8474046
Abstract
Laboratory animals used for experiments need to be monitored closely for signs of pain and disstress. A well-established score is the mouse grimace scale (MGS), a method where defined morphological changes of the rodent's eyes, ears, nose, whiskers and cheeks are assessed by human experts. While proven to be highly reliable, MGS assessment is a time-consuming task requiring manual processing of videos for key frame extraction and subsequent expert grading. While several tools have been presented to support this task for white laboratory rats, no methods are available for the most widely used mouse strain (C56BL6) which is inherently black. In our work, we present a set of methods to aid the expert in the annotation task by automatically processing a video and extracting images of single animals for further assessment. We introduce algorithms for separation of an image potentially containing multiple animals into single subimages displaying exactly one mouse. Additionally, we show how a fully convolutional neural network and a subsequent grading function can be designed in order to select frames that show a profile view of the mouse and therefore allow convenient grading. We evaluate our algorithms and show that the proposed pipeline works reliably and allows fast selection of relevant frames.
Involved external institutions
Germany (DE)How to cite
APA:
Kopaczka, M., Ernst, L., Heckelmann, J., Schorn, C., Tolba, R., & Merhof, D. (2018). Automatic Key Frame Extraction from Videos for Efficient Mouse Pain Scoring. In 2018 5th International Conference on Signal Processing and Integrated Networks, SPIN 2018 (pp. 248-252). Noida, IND: Institute of Electrical and Electronics Engineers Inc..
MLA:
Kopaczka, Marcin, et al. "Automatic Key Frame Extraction from Videos for Efficient Mouse Pain Scoring." Proceedings of the 5th International Conference on Signal Processing and Integrated Networks, SPIN 2018, Noida, IND Institute of Electrical and Electronics Engineers Inc., 2018. 248-252.
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