Generating Saliency Maps from Grayscale Video Frames Using OMP Algorithm
This project focuses on an innovative approach to create visual saliency maps by processing two frames of grayscale video. Using a dictionary technique, an 8x8 matrix is generated to extract a sparse matrix frame by frame. The sparse matrix will be reshaped and normalized to derive meaningful results from video patches. The implementation involves combining images into a video array for visualization in MATLAB. Future work will explore color video testing using the OMP algorithm to enhance saliency map generation techniques.
Generating Saliency Maps from Grayscale Video Frames Using OMP Algorithm
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Presentation Transcript
Visual Saliency Update LaTia Jefferson NasimSouly
Results: Process to Reach Create patches from two frames and the window of 8 x 8 Use the dictionary of grayscale video to return a result matrix Extract a sparse matrix (frame by frame from the result matrix) Reshape and normalize the sparse matrix to get results
Code Combine sequence images into a video array and play in Matlab Video patches in grayscale and color Going to try working with the OMP Box algorithm to generate a sparse matrix On a search for color video for testing and generating saliency maps
