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VOOZH | about |
Computer Vision library for human-computer interaction. It implements Head Pose and Gaze Direction Estimation Using Convolutional Neural Networks, Skin Detection through Backprojection, Motion Detection and Tracking, Saliency Map.
This project provides a tool to compare two images using various similarity metrics, including histograms, structural similarity index (SSIM), mean squared error (MSE), mean absolute error (MAE), feature matching, and image hashing.
Detection of people in a video sequence using histogram analysis
This project is about Histogram Equalization and Contrast Stretching
We are working on Object detection and extraction from Surveillance Camera Footage.After extracting the object of our interest , we want to compare their their Normalized color Histograms using Chi Square Method. Implementation of various Tracking Methods
Project utilizing histograms to identify individuals within a pre-detected video sequence of images using OpenCV.
Computation of image histogram, histogram equalization, comparison, and matching.
Read images, compute bins, generate image histograms, which involves equalising a 64-bin grayscale histogram and comparing and matching the two histograms.
Standalone test implementation of set-to-set histogram similarity comparisons with CUDA GPU acceleration
A comparative study of 5 different color detectors (the goal is to detect of the prominent color in the image).
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