The invention discloses a
data processing method and
system for realizing moving
object detection and
behavior recognition, and relates to the technical field of
computer data processing, and the method comprises the steps: collecting multi-
source data, and carrying out the denoising,
point cloud outlier elimination and normalization
processing; performing initial detection on a moving object, optimizing an anchor frame by using improved YOLOv8, and performing space-time matching with an image candidate frame after
radar clustering; multi-dimensional
feature extraction: extracting space-time, attitude and attribute features and splicing the space-time, attitude and attribute features into feature vectors; training and reasoning a
behavior recognition model, constructing a
hybrid model for training, and reasoning an output behavior category and confidence; optimizing a result, dynamically adjusting a confidence coefficient threshold value, performing multi-source
verification and matching an abnormal rule; and outputting and feeding back a result, visually outputting and alarming, and storing a log to support retrieval. According to the method, environmental interference is solved through multi-source fusion, the anchor frame is optimized, missing detection is reduced, the model gives consideration to precision and speed, abnormal misjudgment is reduced through multi-source
verification, and the method is adaptive to multiple scenes.