This paper introduces an ongoing project that is developing the Blyzer framework, a generic, video-based approach for automatic analysis of animal behavior. The field of veterinary healthcare informatics is still in its early stages, and state-of-the-art solutions from human healthcare are not easily adaptable. The Blyzer framework addresses this by providing a low-cost, simple solution that can be reused across various animal species and analytical tasks, supporting the call for more objective and quantifiable behavior assessment. It comprises two main layers: a computer vision module for tracking animals and a sense-making module for interpreting the extracted data based on health-related tasks. A concrete application of this framework is its use in decision support for behavioral veterinarians, particularly for objectively assessing conditions like ADHD-like behavior in domestic dogs by measuring erratic movement during consultations. The authors emphasize the potential for this framework to facilitate the growth of animal health informatics, promote digitalization in veterinary science and animal welfare, and encourage cross-fertilization between human and animal health informatics.
Non-Invasive Computer Vision-Based Fruit Fly Larvae Differentiation: Ceratitis capitata and Bactrocera zonata
This paper proposes a novel, non-invasive method using computer vision
