Before revision:  Our method is able to distinguish and classify videos from various environmental conditions . We use sliding window embeddings (time delay embeddings), persistent homology, average persistence landscapes, and support vector machines .
After revision:  Our method is able to distinguish and classify videos from various environmental conditions and we analyze the trade-off between accuracy and interpretability. Furthermore, we present a novel technique for visualizing the outputs of our analysis in terms of the input. Specifically, we use representative cycles of persistent homology to produce synthetic videos of stereotypical behaviors .