Explore MATLAB source code curated for "视频序列" with clean implementations, documentation, and examples.
Utilizing the median method to extract initial background from video sequences, which serves as a fundamental preprocessing step in video processing for background extraction and real-time updating. This approach involves statistical analysis of pixel values across multiple frames to establish a robust baseline.
A MATLAB implementation of Kalman filter-based tracking for video sequence frames, featuring state-space modeling and recursive prediction-correction algorithms for object motion trajectory analysis.
Design a deinterlacing algorithm to convert an interlaced video sequence into a progressive scan format video, including implementation considerations for pixel processing and frame relationships.
MeanShift for Object Tracking in Video Sequences: Implementation and Manual Target Selection Techniques
MATLAB implementation of motion estimation and compensation algorithms for video sequences, featuring block matching techniques and motion vector optimization
Motion Detection in Video Sequences: Implementation of single-object motion detection using frame differencing method with code-level algorithmic explanations.
Implementation of target tracking using the Meanshift algorithm, which extracts the first frame from video sequences, defines target regions, performs tracking, and dynamically displays tracking results with color histogram matching and iterative convergence
Object detection using background reconstruction techniques, including video sequence detection demonstrations
This is the source code implementation of the Kalman filter algorithm, primarily designed for predictive tracking in video sequences. The implementation includes state prediction and measurement update functions with detailed parameter configuration.
Comprehensive MATLAB-based gait recognition resources including algorithm implementations, video sequences, presentation materials, and relevant research literature