We present an application for analyzing motion in sequential video frames, crucial for camouflaged object detection in ecological research and surveillance. Our tool integrates image processing, composite visual representation, and coordinated interactions into a visualization pipeline. It calculates frame differences using E-measure, MAE, and SSIM image metrics, visually encoding these as pixels or marks in superimposed foreground and background layers. Applied to videos of camouflaged wildlife, this approach demonstrates potential for camouflage detection and advances the integration of abstract and realistic visual representations for effective motion analysis.