To overcome the mentioned limitations - animal specific algorithms, slow algorithms that operate only offline, and low accuracy - we developed a new online algorithm called ToxId. In these situations the use of an online tracking is required 19. Thus, offline tracking is generally slow and cannot be applied in real-time, streaming applications, or other situations where only the current frame can be accessed. These techniques are computationally and memory expensive and require access to past and future frames (offline tracking). Other approaches to reduce occlusion problems rely on pattern recognition, matching specific texture maps 6 or using convolutional neural networks 18 to identify the animals. Nevertheless these methods can only be applied for animals geometrically compatible with the used model. Additionally, some authors discuss the use of features such as face properties 16 or bilateral symmetry 17. To improve detection and tracking, some techniques use a specific model of the animal body based on the head shape 10, 11, the body geometry 12, 13, 14 or the symmetry axis 15. This technique adds complexity to the experimental setup and dramatically increases the amount of data generated. Other methods rely on improving the detection by using several cameras with different perspectives 8, 9. These solutions, however, may be invasive and are not applicable to the vast majority of animals. To address the occlusion problem, some techniques tag the organisms with a visual marker to preserve their identity 7.
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