942 People – Passenger Behavior Recognition Dataset (RGB & Infrared)

passenger behavior recognition dataset

abnormal passenger behavior dataset

in-cabin monitoring dataset

RGB IR passenger dataset

automotive AI passenger monitoring

motion sickness detection dataset

sleepiness detection dataset

passenger safety AI dataset

The 942 passenger behavior recognition dataset covers multiple ages, time periods and light exposure. Passenger behavior includes passenger normal behavior, passenger abnormal behavior (passenger motion sickness behavior, passenger sleepiness behavior, passenger lost children & items behaviors). In terms of acquisition equipment, visible and infrared binocular cameras are used. This dataset is suitable for passenger activity recognition, abnormal behavior detection and other tasks.

This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.

Specifications

Data size

942 people

Population distribution

gender distribution: 503 males, 439 females; race distribution: Asian; age distribution: 18~45 years old, 46~60 years old, over 60 years old

Collecting environment

in-car Cameras

Data diversity

multiple age groups, multiple time periods, multiple lighting, multiple behaviors (normal behaviors, carsick behaviors, sleepy behaviors, lost children & items behaviors)

Device

visible light and infrared binocular camera, resolution 1,920x1,080

Shooting position

the center of rear view mirror inside the car, above the right A-pillar in the car, front passenger position, above the left B-pillar in the car, above the right B-pillar in the car, rearview mirror wide angle lens position

Collecting time

day, evening, night

Collecting light

normal light, weak light, strong light

Vehicle Type

Car, SUV, MVP, Truck, Bus

Data Format

the video data format is .mp4

Accuracy

according to the accuracy of each person's acquisition action, the accuracy exceeds 95%;the accuracy of label annotation is not less than 95%

What types of computer vision applications can Nexdata’s datasets support?

Nexdata’s computer vision datasets support a wide range of AI applications, including image classification, object detection, image segmentation, facial and human-related recognition, scene understanding, autonomous driving, and other visual perception tasks. Depending on the dataset, data may include images, videos, bounding boxes, polygons, keypoints, segmentation masks, text annotations, and other structured labels.

Can Nexdata customize Computer Vision datasets based on our specific requirements?

Yes. If our off-the-shelf Computer Vision datasets do not fully meet your requirements, Nexdata provides flexible custom data collection, annotation, and curation services. We can customize data based on your target objects, environments, scenarios, camera specifications, geographic locations, data volume, annotation formats, and quality standards to support specific model training and evaluation needs.

How does Nexdata ensure the quality and scalability of its Computer Vision datasets?

Nexdata applies multi-stage quality control throughout data collection, annotation, validation, and delivery. Depending on project requirements, we can implement customized annotation guidelines, multi-level reviews, consistency checks, and quality sampling to ensure dataset accuracy and consistency. Our data collection and processing capabilities can also be scaled to support large-volume Computer Vision projects.

942 People – Passenger Behavior Recognition Dataset (RGB & Infrared)

passenger behavior recognition dataset abnormal passenger behavior dataset in-cabin monitoring dataset RGB IR passenger dataset automotive AI passenger monitoring motion sickness detection dataset sleepiness detection dataset passenger safety AI dataset

Current Project Maturity

passenger behavior recognition dataset

abnormal passenger behavior dataset

in-cabin monitoring dataset

RGB IR passenger dataset

automotive AI passenger monitoring

motion sickness detection dataset

sleepiness detection dataset

passenger safety AI dataset