A Novel Approach To Detect and Track Small Animals using YOLOv8 and DeepSORT

This paper introduces a novel approach for the segmentation, detection, and tracking small animals and insects like butterflies and squirrels using the YOLOv8 object detection model and Deep SORT tracking algorithm. With a high recall score of 0.9, the proposed methodology enables accurate detection and tracking of these creatures. Tracking small insects and animals like butterflies and squirrels is crucial for understanding their ecology and implementing effective conservation strategies. The results demonstrate its ability to accurately track these creatures across diverse settings, including varying lighting conditions and backgrounds. The proposed methodology approach offers several advantages over existing methods. It enables tracking of both air and land-based creatures, surpasses the accuracy of hand-crafted feature-based approaches. The findings highlight the potential of our approach for butterfly and squirrel tracking, advancing ecological studies and contributing to species preservation. The Big Butterfly Count serves as a valuable resource for tracking butterflies and supporting their conservation efforts.