This research uses computer vision and machine learning for implementing a fixed-wing-uav detection technique for vision based net landing on moving ships. A rudimentary technique using SIFT descriptors, Bag-of-words and SVM classification was developed during the study.
Bag-of-Features model for image classification (Octave)
UB Computer Vision
A computer vision application that retrieves the most similar video frames to selected image/object/character
Content-Based Image Retrieval (CBIR) is a challenging task which retrieves the similar images from the large database. Most of the CBIR system uses the low-level features such as color, texture and shape to extract the features from the images. In Recent years the Interest points are used to extract the most similar images with different view po…
A from-scratch implementation of image classification system using Harris detector and Bag of words method.
Computer Vision techniques on Photmetric Stereoand Color, Neighborhood Processingand Filters, Harris Corner Detector and Optical Flow, Image Alignment and Stitching, Bag-of-Words and CNNs for Image Classification.
This system uses the bag-of-words approach with its Spatial Pyramid Extension for classifying the given image into 8 types of scenes.
A Bag of Visual Words reproduction of the ICCV of 2005 in MATLAB as a part of my thesis research
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