单目SLAM，用于地下停车场建图

ML classifier trained with raw pixels as features and high level features and then comparing their accuracies

[Project] A computer vision tool for identifying Buddha statues around Phra Pathom Chedi using image feature matching (ORB, SIFT, AKAZE, KAZE). Includes a Tkinter GUI and a dataset of annotated images for similarity comparison.

Codes regarding the paper: Handwritten Image Detection using DCGAN with SIFT and ORB Optical Features

Detection of ORB features Matlab. Example with Webcam and drone in Simulink.

Coin identification and recognition systems may drammatically enhance the extended operation of vending machines, pay phone systems and coin counting machines. The primary purpose of this project is to develop a detector capable of finding and classifying Euro coins in images purely relying on Computer Vision based frameworks.

Using features-matching algorithm for tracking object

Fast-bag-of-words ROS wrapper for feature-based place detection and relocalization.

Code for beer label classification using SIFT and ORB

Implementation of different Kalman Filters to estimate the state of the quadrotor using optical flow and IMU.

Cybervision can generate a 3D model from two photos of an object

Implementation of Panorama stitching using ORB feature matching, and RANSAC for homography estimation, and stitching using Image pyramids.