Unlock the Power of
Video Data for AI

Eyeverse experts perform object tracking by drawing cubes around objects. This allows systems to recognize a given object’s length, width, and height.

Event tracking annotates specific actions or events within a video. This helps in recognizing patterns and understanding interactions in various scenarios.

Semantic segmentation in video annotates each pixel across frames, providing a comprehensive understanding of the scene. This technique is vital for detailed scene analysis.

Pose estimation annotates the positions of key points on the human body or other objects across video frames. This is crucial for analyzing motion and interactions.

Activity recognition involves labeling specific activities or behaviors in a video. This helps in understanding complex interactions and behaviors in various contexts.

Lane annotation marks the boundaries and centerlines of lanes on roadways within video frames. This is essential for advanced driver assistance systems (ADAS).

Temporal segmentation divides a video into segments based on specific criteria, such as scene changes or events. This helps in organizing and analyzing video efficiently.

Keyframe annotation involves annotating only specific frames that represent significant changes within a video. Efficient for long videos with recurring patterns.