Datasets

CVC Multimodal Stereo Dataset (1)

Brief Description

CVC-Multimodal Stereo Dataset (1) consists of three subsets of multimodal stereo images (visible and infrared), each one containing a different family of scenarios: Roads, Facades, and Smooth Surfaces. Each subset contains images taken in different conditions and days. For every couple of multimodal stereo images a real or a synthetic depth map, to be used as a ground truth, is given. Additionally, the corresponding calibration sets are also provided.

The images have been recorded using a multimodal stereo rig with the following characteristics:

• Color camera: Sony ICX084 Bayer pattern CCD, 6mm focal length lens, 640x480 image resolution (Bumblebee 2 stereo).
• Infrared camera: PathFindIR Flir camera, 19mm focal length lens (36 degree HFOV), 534x426 image resolution.

All the images are provided in lossless PPM and BMP format.

References to this database should be made to the following publication:

• Barrera F., Lumbreras F. and Sappa A., "Multimodal Stereo Vision System: 3D Data Extraction and Algorithm Evaluation", IEEE Journal of Selected Topics in Signal Processing, Vol. 6, No. 5, September 2012, pp. 437-446.

CVC Multimodal Stereo Dataset (2)

Brief Description

CVC-Multimodal Stereo Dataset (2) consists of 100 pairs of VS-LWIR images. All the images were rectified and aligned so that matches should be found in horizontal lines. The data set contains outdoor images of different urban scenarios.

The images have been recorded using a multimodal stereo rig with the following characteristics:

• Color camera: Sony ICX084 Bayer pattern CCD, 6mm focal length lens, 640x480 image resolution (Bumblebee 2 stereo).
• Infrared camera: PathFindIR Flir camera, 19mm focal length lens (36 degree HFOV), 534x426 image resolution.

All the images are provided in lossless BMP format.

References to this database should be made to the following publications:

• Barrera F., Lumbreras F. and Sappa A., "Multispectral Piecewise Planar Stereo using Manhattan-World Assumption", Pattern Recognition Letters, Vol. 34, No.1, January 2013, pp. 52-61.
   
• Aguilera C., Barrera F., Lumbreras F., Sappa A., and Toledo R., “Multispectral Image Feature Points”, Sensors, Vol 12, No. 9, September 2012, pp. 12661-12672.