Willow. Vocab 3db. Collection of 33 Kinect (RGB+D) datasets with 6D ground truth (by the CVPR team @ Technische Universitat Munchen) | The Mobile Robot Programming Toolkit. Berkeley 3-D Object Dataset. Microsoft - Action Recognition Dataset - Zicheng Liu. MSR Action Recognition Datasets and Codes HON4D Code and MSRActionPairs Dataset MSRGesture3D (28MB): The dataset was captured by a Kinect device. There are 12 dynamic American Sign Language (ASL) gestures, and 10 people. Each person performs each gesture 2-3 times. . {7,8,9} ->"ASL_Where"; {10,11,12} ->"ASL_Store"; {13,14,15} ->"ASL_Pig"; {16,17,18} ->"ASL_Past"; {19,20,21}->"ASL_Hungary"; {22.23,24}->"ASL_Green"; {25.26.27}->"ASL_Finish"; {28,29,30}->"ASL_Blue"; {31,32,33}->"ASL_Bathroom"; {34,35,36}->"ASL_Milk"; Each file is a MAT file which can be loaded with 64bit MATLAB.
X=load('sub_depth_01_01'); width = size(x.depth_part,1); height = size(x.depth_part,2); nFrames = size(x.depth_part,3); for(i=1:width) for(j=1:height) for(k=1:nFrames) depthval = x.depth_part(i,j,k); end end end The following two papers reported experiment results on this dataset: Alexey Kurakin, Zhengyou Zhang, Zicheng Liu, A Real-Time System for Dynamic Hand Gesture Recognition with a Depth Sensor, EUSIPCO, 2012. Part 1 (440 MB) ETH - kinect:iros2011kinect – ASL Datasets.
You can download the 2.6 GB .tar.bz2 file. The images above show the 3 different experimental setups. This dataset is the companion of our 2011 IROS paper (full text). This dataset contains 27 ROS bags of point clouds produced by a Kinect based the ground truth obtained from a Vicon pose capture system. These runs cover 3 environments of increasing complexity, with 3 types of motions at 3 different speeds. This dataset can be used with our ICP Mapper to track the pose of the Kinect and to explore parameters of ICP algorithms.
This dataset is linked to the following paper: F. This assume that you have the ROS package ethzasl_icp_mapping installed. Here is a quick way to test it: $ roscore & $ rosparam set use_sim_time true $ cd <your data set repository> $ rosbag play --clock --pause 0high-0slow-0fly-0_2011-02-19-11-44-41.bag In an other console: $ roscd ethzasl_icp_mapper/launch/openni/IROS_2011 $ roslaunch tracker.launch Finally, to view what is going on: TUM - Computer Vision Group - Dataset Download. NYU- Depth V2 « Nathan Silberman. Nathan Silberman, Pushmeet Kohli, Derek Hoiem, Rob Fergus If you use the dataset, please cite the following work: Indoor Segmentation and Support Inference from RGBD Images ECCV 2012 [PDF][Bib] Samples of the RGB image, the raw depth image, and the class labels from the dataset.
Overview The NYU-Depth V2 data set is comprised of video sequences from a variety of indoor scenes as recorded by both the RGB and Depth cameras from the Microsoft Kinect. 1449 densely labeled pairs of aligned RGB and depth images 464 new scenes taken from 3 cities 407,024 new unlabeled frames Each object is labeled with a class and an instance number (cup1, cup2, cup3, etc) The dataset has several components: Labeled: A subset of the video data accompanied by dense multi-class labels. Downloads Labeled Dataset Output from the RGB camera (left), preprocessed depth (center) and a set of labels (right) for the image. The labeled dataset is a subset of the Raw Dataset. Raw Dataset / .. Toolbox Raw Dataset Parts. Kinect@Home. Untitled. Www.cas.kth.se/rgb-d/ RGB-D work and datasets at CAS/KTH Exploiting and modeling local 3D structure for predicting object locations We have constructed our dataset from five different sites in Europe; the Technical University of Vienna (TuV), the University of Birmingham (UB), the Royal Institute of Technology (KTH), the German Center for Artificial Intelligence in Saarbrucken (DFKI) and the University of Ljubljana (UL).
Downloading the data set To access the dataset drop me a line at aydemir@kth.se , it will be available for direct download as well, we're just in the process of allocating more space in the webserver for it. 3D mapping with the dataset We have also built a method to construct 3D maps, using the dataset. Example images from the dataset.