An attempt to implement the SIFT paper for key-point detection
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Updated
Sep 15, 2019 - Python
An attempt to implement the SIFT paper for key-point detection
A new approach to multi-scale template matching using key-point matching and perspective-transformations
Car collision detection system using computer vision techniques. For this purpose, a feature tracking/mathing system is implemented using various detector / descriptor pairs
Keypoint detection matlab demo
SOLOv2: Dynamic, Faster and Stronger. achieve 37.2mAP on coco val (res50,36 epoch) Adding keypoints
The implementation of part of the ORB (Oriented FAST and Rotated BRIEF) pipeline. The ORB consists of the feature detector and feature descriptor that detect and describe reproducible and discriminative regions in an image. Those, in turn, can be matched between pairs of images for correspondence search, 3D reconstruction, and so on.
Human-Machine Interaction Course Demos
Keypoint-matching (AKAZE method) using OpenCV library
Estimating trajectory using RGB-D images
This project contains code and explanation behind the code for detecting 15# facial keypoints for a given face image (Kaggle dataset) using Multi Layer Perceptron in Julia.
3D object tracking using keypoint detection and feature matching, lidar point cloud data, and image classification using YOLO deep learning model.
Keypoint Tracking and Matching in Autonomous Vehicles to measure TTC between consecutive frames of the KITTI Dataset
A simple and minimal posenet inference in python
Build the feature tracking part of a collision detection system, and test various combinations of keypoint detectors and descriptors to see which combinations perform best.
Object detection
PyTorch data loader that crops persons (with their body landmarks) from COCO dataset.
PyTorch-based toolkit for landmark detection
Monitor Your Workout through a Webcam/IP Camera. No equipment is required, other than a camera and a laptop. This application could potentially replace a personal trainer, making it the idea app for workout.
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