Automatic Estimation of Dog Age: The DogAge Dataset and Challenge
Automatic age estimation is a challenging problem attracting attention of the computer vision and pattern recognition communities due to its many practical applications. Artificial neural networks, such as CNNs are a popular tool for tackling this problem, and several datasets which can be used for training models are available.
Despite the fact that dogs are the most well studied species in animal science, and that ageing processes in dogs are in many aspects similar to those of humans, the problem of age estimation for dogs has so far been overlooked. In this paper we present the DogAge dataset and an associated challenge, hoping to spark the interest of the scientific community in the yet unexplored problem of automatic dog age estimation.
KeywordsCNN Computer vision Applications of deep learning Age estimation
This work has been supported by the NVIDIA GPU grant program.
- 1.Mauger, E., Russell, R.: Anxiety and impulsivity: factors associated with premature graying in young dogs. PLoS ONE 8(3) (2013)Google Scholar
- 8.Iandola, F.N., Han, S., Moskewicz, M.W., Ashraf, K., Dally, W.J., Keutzer, K.: Squeezenet: alexnet-level accuracy with 50x fewer parameters and \(<\)0.5mb model size. arXiv:1602.07360 (2016)
- 11.Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., Wojna, Z.: Rethinking the inception architecture for computer vision. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2818–2826 (2016)Google Scholar
- 12.Wang, X., Guo, R., Kambhamettu, C.: Deeply-learned feature for age estimation. In: 2015 IEEE Winter Conference on Applications of Computer Vision, WACV 2015, Waikoloa, HI, USA, 5–9 January 2015, pp. 534–541 (2015). https://doi.org/10.1109/WACV.2015.77