Dataset: RGB-D Images for Real-World and Synthetic Object Scenes

This dataset consists of both real-world and synthetic RGB-D images, designed for object detection, classification, and segmentation tasks, particularly for primitive shape recognition.

Real-World Data

• Objects: 50 distinct objects captured using a Kinect camera.
• Scenes: The dataset includes both single objects and piles of objects stacked over each other.
• Images: Approximately 300 RGB-D images have been collected.
• Data Format: RGB images paired with corresponding depth images.

Synthetic Data

• Simulator: The synthetic dataset was automatically generated using the CoppeliaSim simulator.
• Objects: Only primitive shapes, including cuboid, semisphere, sphere, cylinder, stick, ring, and cone.
• Scenes: Objects are dropped over each other to form complex scenes.
• Images: The dataset contains 10,000 unique RGB-D images generated by the simulator.

Labels

Both the real-world and synthetic datasets are labeled with geometric primitive shape classes and boundaries, including:

• Cuboid
• Semisphere
• Sphere
• Cylinder
• Stick
• Ring
• Cone

This dataset is designed to support research in grasp detection, object recognition, and scene understanding using RGB-D data.