Multimodal Driver Action Dataset for Distraction Analysis

3MDAD is a multimodal, multiview, and multispectral dataset focused on driver actions and distraction. It contains video and image data from multiple camera perspectives and spectral bands for analyzing driver behavior. The dataset was created for research in automotive safety and computer vision.

Use Cases

• Classify driver distraction states using multiview video streams.
• Train action recognition models on multispectral image data from vehicle cabins.
• Develop multimodal fusion models combining different visual perspectives for robust behavior analysis.
• Benchmark performance of deep learning architectures on driver action recognition tasks.

Strengths

• Multimodal data collection includes multiple camera views.
• Dataset incorporates multispectral imaging for enhanced feature analysis.

Limitations

• Specific sample size, row count, and data volume are unknown.
• Geographic origin and demographic diversity of drivers are unspecified.

Provenance

Source

Kaggle