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RGBD Object
Classification
Common
|...
License: Unknown

Overview

RGB-D Object Dataset

  • The RGB-D Object Dataset is a large dataset of 300 common household objects. The objects
    are organized into 51 categories arranged using WordNet hypernym-hyponym relationships (similar
    to ImageNet). This dataset was recorded using a Kinect style 3D camera that records synchronized
    and aligned 640x480 RGB and depth images at 30 Hz. Each object was placed on a turntable and
    video sequences were captured for one whole rotation. For each object, there are 3 video sequences,
    each recorded with the camera mounted at a different height so that the object is viewed from
    different angles with the horizon.

  • Unlike many existing datasets,such as Caltech 101 and
    ImageNet, objects in this dataset are organized into both categories and instances. In these
    datasets, the class dog contains images from many different dogs and there is no way to tell
    whether two images contain the same dog, while in the RGB-D Object Dataset the category soda
    can is divided into physically unique instances like Pepsi Can and Mountain Dew Can. The dataset
    also provides ground truth pose information for all 300 objects.

RGB-D Scenes Dataset v.2

  • The RGB-D Scenes Dataset
    v2 consists of 14 scenes containing furniture (chair, coffee table, sofa, table) and a subset
    of the objects in the RGB-D Object Dataset (bowls, caps, cereal boxes, coffee mugs, and soda
    cans). Each scene is a point cloud created by aligning a set of video frames using Patch Volumes
    Mapping*. These 3D reconstructions and ground truth object annotations are exactly those used
    in our ICRA 2014 paper (see README).

RGB-D Scenes Dataset

  • This dataset contains 8 scenes annotated with objects
    that belong to the RGB-D Object Dataset. Each scene is a single video sequence consisting of
    multiple RGB-D frames.

Data Format

rgbd-dataset

This part of the dataset contains the cropped RGB-D frames that tightly include the object
as it is spun around on a turntable. There is another part of the dataset available containing
3D point clouds, in PCD format readable with the ROS Point Cloud Library (PCL), as well as
a part containing the full 640x480 images from sensor.

rgbd-dataset_pcd

This part of the dataset contains the
3D point clouds of views of each object, in PCD format readable with the ROS Point Cloud Library
(PCL). There is a part of the dataset available containing cropped images of the objects for
extracting visual features, and another part of the dataset containing the full 640x480 images
from the sensor.

rgbd-dataset_full

This part of the dataset contains the full 640x480 RGB-D frames. There is
another part of the dataset available containing the cropped images of just the object on the
turntable. There is also a part of the dataset with the 3D point clouds of views of each object
in PCD format, readable with ROS Point Cloud Library (PCL).

rgbd-dataset_poses

This part of the dataset contains
the ground truth pose labels for every image in the RGB-D Object Dataset, exactly as used in
the pose recognition evaluation of the AAAI-11 paper (see README).

rgbd-dataset-eval

This part of the dataset
contains the cropped RGB-D frames that tightly include the object, exactly as used in the object
recognition evaluation of the paper introducing the RGB-D Object Dataset (i.e. subsampled every
5th video frame). Use this dataset if you wish to compare directly against object recognition
results published in our papers. There is a separate download for the full dataset containing
all RGB-D frames.

Scenes Dataset

  • rgbd-scenes-v2_pc.zip
    Aligned scene point clouds, ground truth annotations, and camera pose
    estimates from 3D scene reconstruction

  • rgbd-scenes-v2_imgs.zip

    All RGB and depth image frames

  • objects_3dwarehouse.zip
    Point clouds of Trimble 3D Warehouse objects used for
    learning HMP3D features and classifiers in our ICRA 2014 paper, in PLY format (see README).

Data Summary
Type
Video, Depth, Image,
Amount
--
Size
111.45GB
Provided by
University of Washington
The University of Washington is a public research university in Seattle, Washington, United States. Founded in 1861, Washington is one of the oldest universities on the West Coast
| Amount -- | Size 111.45GB
RGBD Object
Classification
Common
License: Unknown

Overview

RGB-D Object Dataset

  • The RGB-D Object Dataset is a large dataset of 300 common household objects. The objects
    are organized into 51 categories arranged using WordNet hypernym-hyponym relationships (similar
    to ImageNet). This dataset was recorded using a Kinect style 3D camera that records synchronized
    and aligned 640x480 RGB and depth images at 30 Hz. Each object was placed on a turntable and
    video sequences were captured for one whole rotation. For each object, there are 3 video sequences,
    each recorded with the camera mounted at a different height so that the object is viewed from
    different angles with the horizon.

  • Unlike many existing datasets,such as Caltech 101 and
    ImageNet, objects in this dataset are organized into both categories and instances. In these
    datasets, the class dog contains images from many different dogs and there is no way to tell
    whether two images contain the same dog, while in the RGB-D Object Dataset the category soda
    can is divided into physically unique instances like Pepsi Can and Mountain Dew Can. The dataset
    also provides ground truth pose information for all 300 objects.

RGB-D Scenes Dataset v.2

  • The RGB-D Scenes Dataset
    v2 consists of 14 scenes containing furniture (chair, coffee table, sofa, table) and a subset
    of the objects in the RGB-D Object Dataset (bowls, caps, cereal boxes, coffee mugs, and soda
    cans). Each scene is a point cloud created by aligning a set of video frames using Patch Volumes
    Mapping*. These 3D reconstructions and ground truth object annotations are exactly those used
    in our ICRA 2014 paper (see README).

RGB-D Scenes Dataset

  • This dataset contains 8 scenes annotated with objects
    that belong to the RGB-D Object Dataset. Each scene is a single video sequence consisting of
    multiple RGB-D frames.

Data Format

rgbd-dataset

This part of the dataset contains the cropped RGB-D frames that tightly include the object
as it is spun around on a turntable. There is another part of the dataset available containing
3D point clouds, in PCD format readable with the ROS Point Cloud Library (PCL), as well as
a part containing the full 640x480 images from sensor.

rgbd-dataset_pcd

This part of the dataset contains the
3D point clouds of views of each object, in PCD format readable with the ROS Point Cloud Library
(PCL). There is a part of the dataset available containing cropped images of the objects for
extracting visual features, and another part of the dataset containing the full 640x480 images
from the sensor.

rgbd-dataset_full

This part of the dataset contains the full 640x480 RGB-D frames. There is
another part of the dataset available containing the cropped images of just the object on the
turntable. There is also a part of the dataset with the 3D point clouds of views of each object
in PCD format, readable with ROS Point Cloud Library (PCL).

rgbd-dataset_poses

This part of the dataset contains
the ground truth pose labels for every image in the RGB-D Object Dataset, exactly as used in
the pose recognition evaluation of the AAAI-11 paper (see README).

rgbd-dataset-eval

This part of the dataset
contains the cropped RGB-D frames that tightly include the object, exactly as used in the object
recognition evaluation of the paper introducing the RGB-D Object Dataset (i.e. subsampled every
5th video frame). Use this dataset if you wish to compare directly against object recognition
results published in our papers. There is a separate download for the full dataset containing
all RGB-D frames.

Scenes Dataset

  • rgbd-scenes-v2_pc.zip
    Aligned scene point clouds, ground truth annotations, and camera pose
    estimates from 3D scene reconstruction

  • rgbd-scenes-v2_imgs.zip

    All RGB and depth image frames

  • objects_3dwarehouse.zip
    Point clouds of Trimble 3D Warehouse objects used for
    learning HMP3D features and classifiers in our ICRA 2014 paper, in PLY format (see README).

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