  Extracting retrievable features from video is of great significance for
structured video database construction, video copyright protection and fake
video rumor refutation. Inspired by point cloud data processing, this paper
proposes a method for marking anything (MA) in the video, which can extract the
contour features of any target in the video and convert it into a feature
vector with a length of 256 that can be retrieved. The algorithm uses YOLO-v8
algorithm, multi-object tracking algorithm and PointNet++ to extract contour of
the video detection target to form spatial point cloud data. Then extract the
point cloud feature vector and use it as the retrievable feature of the video
detection target. In order to verify the effectiveness and robustness of
contour feature, some datasets are crawled from Dou Yin and Kinetics-700
dataset as experimental data. For Dou Yin's homogenized videos, the proposed
contour features achieve retrieval accuracy higher than 97% in Top1 return
mode. For videos from Kinetics 700, the contour feature also showed good
robustness for partial clip mode video tracing.
