With advancements in panoramic camera technology, resolutions have significantly improved [1], capturing distant objects more clearly. The Insta360 Titan, for instance, supports up to 11k resolution ( \(10560\times 5280\) ), offering unprecedented detail. However, current object recognition methods struggle with such ultra-high-resolution footage. This paper presents a novel approach for detecting moving objects in 11k panoramic videos from the Insta360 Titan. Our method involves downsampling and background subtraction to detect moving objects quickly and accurately. These regions are then cropped into smaller images for high-precision detection, reducing computational load. This technique, inspired by proxy methods in video editing, maintains result quality while easing processing burdens. Experiments demonstrate our method’s ability to accurately detect humans at distances up to 60 m, achieving 15 fps, thus proving its effectiveness for ultra-high-resolution panoramic footage.