Dataset asscociated with a paper in Computer Vision and Pattern Recognition (CVPR)

 

"Object classification from randomized EEG trials"

 

If you use this code or data, please cite the above paper.

Instructions: 

See the paper "Object classification from randomized EEG trials" on IEEE Xplore.

 

Code for analyzing the dataset is included in the online supplementary materials for the paper.

 

The code from the online supplementary materials is also included here.

 

If you use this code or data, please cite the above paper.

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336 Views

The LEDNet dataset consists of image data of a field area that are captured from a mobile phone camera.

Images in the dataset contain the information of an area where a PCB board is placed, containing 6 LEDs. Each state of the LEDs on the PCB board represents a binary number, with the ON state corresponding to binary 1 and the OFF state corresponding to binary 0. All the LEDs placed in sequence represent a binary sequence or encoding of an analog value.

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179 Views

The UBFC-Phys dataset is a public multimodal dataset dedicated to psychophysiological studies. 56 participants followed a three-step experience where they lived social stress through a rest task T1, a speech task T2 and an arithmetic task T3. During the experience, the participants were filmed and were wearing a wristband that measured their Blood Volume Pulse (BVP) and ElectroDermal Activity (EDA) signals. Before the experience started and once it finished, the participants filled a form allowing to compute their self-reported anxiety scores.

Instructions: 

Please find more details about the UBFC-Phys dataset's organization in the READ_ME file.

If you use this dataset, please cite the following paper:

 

R. Meziati Sabour, Y. Benezeth, P. De Oliveira, J. Chappé, F. Yang. "UBFC-Phys: A Multimodal Database For Psychophysiological Studies Of Social Stress", IEEE Transactions on Affective Computing, 2021.

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2904 Views

For the task of detecting casualties and persons in search and rescue scenarios in drone images and videos, our database called SARD was built. The actors in the footage have simulate exhausted and injured persons as well as "classic" types of movement of people in nature, such as running, walking, standing, sitting, or lying down. Since different types of terrain and backgrounds determine possible events and scenarios in captured images and videos, the shots include persons on macadam roads, in quarries, low and high grass, forest shade, and the like.

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1027 Views

The early detection of damaged (partially broken) outdoor insulators in primary distribution systems is of paramount importance for continuous electricity supply and public safety. In this dataset, we present different images and videos for computer vision-based research. The dataset comprises images and videos taken from different sources such as a Drone, a DSLR camera, and a mobile phone camera.

Instructions: 

Please find the attached file for complete description

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426 Views

Indirect hand measurement processes have been used to improve remote accessibility and non-contact acquisition methods. This is particularly helpful when developing custom products, such as prostheses or gloves, to a user. Indirect hand measurements, however, may be difficult to acquire due to the requirement that certain specifications to be met. In the case of indirect measurement determination from 3D scans, obstructions may affect the observed outcome. This is especially true when using low-cost 3D scanners that have not been optimized for medical use.

Instructions: 

The data is provided in .xlsx Excel format. It contains one sheet that includes all the hand measurements corresponding with the devices used. Key measurements for each device are summarized in four .txt files, each belonging to a separate scanner. The .R file is included and contains the R code used for statistical analysis of the observed measurements. 

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80 Views

We propose a camera calibration method to generate a high-quality and photorealistic 3D (dimension) volumetric graphics model using several low-cost commercial RGB-D (depth) cameras located in a limited space. We show an efficient workflow to register a model efficiently and propose iterative calibration techniques to construct it. Using multiple frames, calibration in the vertical direction between the upper and lower cameras is performed. After selecting any four pairs, the calibration is performed while rotating with the vertical calibration results from other adjacent viewpoints.

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42 Views

The data and codes show 3D reconstruction of a checkerboard with pseudo-colored errors, using different calibration and reconstruction methods. (1) with general stereo calibration and linear reconstruction, (2) with general stereo calibration and approximately undistorted reconstruction, (3) with stereo calibration and undistorted reconstruction using nonlinear epipolar constraints, and (4) with the residual distortion-calibrated reconstruction. 

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102 Views

The boring and repetitive task of monitoring video feeds makes real-time anomaly detection tasks difficult for humans. Hence, crimes are usually detected hours or days after the occurrence. To mitigate this, the research community proposes the use of a deep learning-based anomaly detection model (ADM) for automating the monitoring process.

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333 Views

The 3DLSC-COVID datset  includes a total of  1,805 3D chest CT scans with more than 570,000 CT slices were collected from 2 standard CT scanners of Liyuan Hospital, i.e.,  UIH uCT 510 and GE Optima CT600.  Among all CT scans, there were 794 positive cases of COVID-19, which were further confirmed by clinical symptoms and RT-PCR from January 16 to April 16, 2020.

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758 Views

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