Pointve

Pointve is a concept used in computer graphics and computer vision to describe a per-point velocity-annotated representation of a dynamic point cloud. In a pointve dataset, each point i has a position p_i and a velocity vector v_i that indicate its instantaneous motion, enabling the description of motion at the level of individual samples rather than at image or voxel granularity.

Origin and meaning: The term blends “point” with “velocity” and is used in discussions of motion-aware point clouds. It is not a universally standardized term and appears in various forms in research on dynamic scenes, real-time rendering, and simulation.

Computation: Pointves are typically derived by tracking points across time, by estimating motion from sequences of 3D scans or stereo imagery, or by learning-based methods that predict per-point motion. Common approaches include probabilistic filters, optical-flow-inspired networks, and temporal smoothing to maintain coherence across frames.

Applications: Pointves support advanced tasks such as motion-aware rendering, physics-based simulation, object tracking in lidar or depth streams, and enhanced fusion of multi-view scans. They facilitate predictive rendering, motion blur synthesis, and more accurate alignment of successive point clouds.

Limitations and challenges: Per-point velocity information is sensitive to noise, occlusions, and point correspondence ambiguities. Storage and computation scale with the number of points and required temporal history, necessitating efficient representations and streaming methods. Relationship to related concepts: Pointwise velocity fields, motion vectors, and dynamic point clouds are related concepts; pointve can be seen as a specific implementation of a per-point motion descriptor.

See also: point cloud, dynamic point cloud, optical flow, motion estimation, per-point attributes.