KFusion: Implementation of KinectFusion
A CUDA-based implementation of KinectFusion for real-time dense surface reconstruction and tracking using a Kinect camera.
What is KFusion: Implementation of KinectFusion?
KFusion is an open-source implementation of the KinectFusion system, which performs real-time dense surface reconstruction and tracking using a Kinect depth camera. It processes depth data through GPU-accelerated algorithms to build and update a 3D volumetric model of the environment. The project solves the problem of creating accurate, real-time 3D maps from a single moving depth sensor.
Researchers and developers working in computer vision, robotics, or augmented reality who need real-time 3D reconstruction capabilities. It is particularly suited for those with CUDA-enabled hardware and Kinect sensors.
Developers choose KFusion for its faithful implementation of the seminal KinectFusion paper, its GPU-optimized performance, and its cross-platform sensor support. It provides a foundational codebase for experimenting with dense SLAM and surface reconstruction without proprietary dependencies.
Overview
This is an implementation sketch of the KinectFusion system described by Newcombe et al.
Use Cases
Best For
- Real-time 3D environment mapping with a Kinect sensor
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