Join GitHub today
GitHub is home to over 28 million developers working together to host and review code, manage projects, and build software together.Sign up
Background subtraction - Joint domain range modeling code
Fetching latest commit…
Cannot retrieve the latest commit at this time.
(1) Instructions to run code (i) Main script is run_domain_range_bg_modeling.m (for color feature model only) or run_domain_range_bg_modeling_hybrid.m (for color-texture hybrid feature model) (ii) Change video number to select appropriate video in above scripts. Note that video_numbers can be an array of video numbers which will be processed in sequence (ii) Change path to input video, input groundtruth, output folder in load_video.m (iii) Set algorithm_to_use variable in the main script (iv) Set any optional parameters in the main script Setting display_general to 1 displays the segmentation for each frame in a figure (v) Run main script in matlab. Note that it may take several hours for complete video sequence to be processed. If you desire to run script for a smaller subset of video frames, change the total_num_frames variable in load_video.m (vi) Output will be saved in the folder specified by output_sequences_folder in load_video.m Output is a mat file with all processed frames, all output frames, bg masks, and some input parameters. (vii) Output video segmentation may be observed by using step_through_color_image_sequence_pair( image_stack, segmented_image_stack); This is automatically invoked if a single video is in video_numbers. If multiple videos are processed, then the user has to load the mat files that were saved and then call step_through_color_image_sequence_pair manually (2) Credits for third-party code used Thanks to Michael Rubinstein for max flow code (obtained from matlabcentral) Thanks to Mark A. Ruzon for RGB2Lab code (obtained from matlabcentral)