Features
Artificial intelligence (AI) is playing a crucial role in driving the digital transformation of our society, especially in the field of computer vision. This technology enables machines to understand and interpret the visual world in a similar manner to humans, which paves the way for innovative applications in a broad array of sectors, including healthcare, security, and the automotive industry.
However, to be truly effective, these systems require extensive and varied training datasets, which are essential for building robust AI models offering improved accuracy. Aware of these challenges, Lynred is actively committed to powering research in this area by providing thermal image datasets, with the goal of advancing computer vision applications and pushing the boundaries of what technology can achieve.
This dataset comprises three parts covering complementary fields:
- Multimodal Detection: for training AI algorithms, with up to nine classes in various weather conditions
- Stereovision: for combining multimodal, stereo thermal IR and stereo visible-light RGB, and tracking (video sequences), with perfectly synchronized images
- Range Estimation: for estimating the pedestrian detection range in various Pedestrian Automatic Emergency Braking (PAEB) conditions, which goes over and above the requirements in current regulations
Description
LYNRED Mobility Dataset: Multimodal Detection
The LYNRED Multimodal Detection Dataset is specifically designed to support the development of Advanced Driver-Assistance Systems (ADAS) and self-driving vehicles by providing a comprehensive collection of thermal and visible-light RGB data. It comprises 8,000 synchronized and aligned infrared and visible-light RGB images captured in a wide range of environmental conditions, including every season, as well as daytime and nighttime scenes. Researchers and engineers can harness this dataset to develop and test their algorithms in real-world driving scenarios.
LYNRED Mobility Dataset: Stereovision
The LYNRED Stereovision dataset includes everything needed to develop algorithms for image registration, visible-thermal fusion and depth estimation. It contains 43,200 images from six video sequences using two thermal and two visible cameras synchronized by an external trigger in various urban, rural, daytime and night-time scenarios.
LYNRED Mobility Dataset: Range Estimation
The LYNRED Range Estimation Dataset provides a large number of sequences of pedestrians crossing the road at multiple distances, captured from a fixed camera viewpoint inspired by the New Car Assessment Program (NCAP) and National Highway Traffic Safety Administration (NHTSA) scenarios, two renowned car safety performance assessment programs. It can be used to evaluate the detection range of a thermal-based PAEB system up to 250 meters, as well as support a varied range of applications relating to pedestrian detection, self-driving vehicles, and ADAS, which goes beyond the scope of the NCAP or NHTSA test protocols.
For more information visit: LYNRED Mobility Dataset
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