Create high-quality, scenario-based video datasets tailored to your AI objectives. Learning Spiral AI supports diverse real-world activities, environments, movements, and interactions to help models interpret motion, track objects, and recognize actions with greater reliability. Our customized data collection approach aligns each dataset with your use case, enabling scalable development and evaluation of computer vision systems for automation, analytics, safety, and intelligent decision-making.
Video
Motion Understanding
Develop video datasets that capture diverse movements, interactions, and environmental conditions to help AI systems understand how people, objects, and machines move over time. These datasets support applications such as gesture analysis, autonomous systems, sports analytics, workplace monitoring, and behavioural intelligence.
Object Tracking
Create scenario-based video data that enables AI models to identify and follow objects accurately across frames. The datasets can include varying camera angles, lighting conditions, speeds, backgrounds, and levels of occlusion to strengthen performance in surveillance, mobility, retail analytics, robotics, and industrial automation.
Activity Recognition
Collect video datasets featuring clearly defined actions and real-world activities to support reliable activity recognition. By covering different participants, locations, perspectives, and conditions, these datasets help AI models recognize human behaviour, operational tasks, safety events, and domain-specific activities with greater consistency.
AI Model Development
Provide customized video data aligned with specific AI model requirements, use cases, and performance goals. High-quality, relevant, and well-structured datasets support model training, testing, validation, and continuous improvement, helping computer vision teams build more accurate and dependable solutions.