VGM-Dataset: Microphone Calibration (MicCal)

We present a dataset used in the paper “A Closed Form Solution to the Microphone Position Self-Calibration Problem” (ICASSP 2012) for the calibration of microphone and sound source events position. The dataset contains the time of arrival of the sound events, the final calibration results and the ground truth obtained using a VICON motion capture system. For details please check the description in the .zip file and cite the paper if you use the dataset for your experiments. 

Download link: VGMMic dataset (mic_cal.zip)

VGM MicCal Microphone Calibration Dataset image 2

VGM-Dataset: 6D Pose of Texture-less Objects (ICRA 2016)

We present a dataset for estimating the 6D pose of texture-less objects from sequences of images. Each object in the dataset is composed of a 3D model (in STL format), and a sequence of images annotated with ground-truth. The ground-truth of each image consists in a rigid body transformation (rotation and translation) representing the 3D motion between the object and the world coordinates systems. These ground-truth poses have been accurately estimated using a VICON motion-capture system.

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VGM-Dataset: 3D room reconstruction with sound

The present database provides a benchmark for evaluating algorithms for room geometry reconstruction from audio. Data are related to a rectangular room with vaulted ceiling of dimensions about 8.5 x 7 x 7.5 m in which 12 microphones and 17 sources have been deployed in a 3 x 3 m central area. High precision ground truth positions of microphones, sources and planar surfaces of the room (i.e. the four walls, the ceiling and the floor) are provided. In particular ground truth source and microphone positions are acquired by a VICON motion capture system while room geometry is reconstructed by a Leica C10 3D laser scanner. Common markers were used to register source and microphone positions with respect to room geometry.

vgm 3droom dataset image 1  vgm 3droom dataset image 2  vgm 3droom dataset image 3
 

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