Process (read and write) depth data, RGB images directly from inter realsense camera or .bag files.
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Updated
Jul 14, 2023 - Python
Process (read and write) depth data, RGB images directly from inter realsense camera or .bag files.
An autonomous intelligent robotic delivery system
Real-time Background Segmentation with Depth Camer
Intel Realsense Camera Code
This repository showcases the integration of various technologies, including the UR3 robotic arm, Intel D435F camera, custom-made gripper, and other components for berry harvesting applications. The project aims to develop a robust system that can detect berries, determine their pose, and execute precise gripping and harvesting actions
Recording Camera Feed using Intel Realsense Camera
Projects demonstrating the possibilities of multiple-reality - merging virtual-reality and the real world
E-waste non-destructive disassembly Robot that approaches and engage with screws.
The project represents a research application for the University of Glasgow Human Computer Interaction (GIST) Group for researching the benefits of dynamic of audio designs in reaching for blind and visually impaired people.
Reconstruction of office from a set of 3D point clouds
simulates Intel realsense camera in Gazebo and ROS
ROS Wrapper for Intel RealSense ID Devices
The API utilizes the power of the Intel Realsense depth camera. Thanks to infrared sensors, the camera is able to calculate the distance and return the three-dimensional coordinates (x, y, z) of a detected person.
Gesture-Enabled Remote Communication and Collaboration
Dobot CR5 with Intel Realsense D435i for object detection and pose estimation (bin-picking application).
This is the repository for TIR-ANT's source-code, a ROS2-based tracked mobile robot capable of SLAM using a 2D LiDAR and a depth camera.
Detection and Ranging of Faces using Intel Realsense Camera and Haar Cascade Detection via OpenCV
official dataset for the Tufts Gaze Depth Dataset, as presented in the paper Gaze Depth Estimation for Eye-Tracking Systems
Development of a high-speed (25km/h) 1/10 scale autonomous electric mobile robot using the Nvidia Jetson, Intel Realsense and Hokuyo Lidar
We have created our own dataset with the help of Intel T265 by modifying the examples given by Intel RealSense.
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