CoCap: Coordinated motion Capture for multi-actor scenes in outdoor environments

TL;DR

CoCap introduces a coordinated multi-view motion capture system for outdoor multi-actor scenes, effectively handling occlusions and obstacles by planning view coordination inspired by Conflict-Based Search, improving accuracy and real-time performance.

Contribution

The paper presents CoCap, a novel multi-view motion capture method that coordinates camera views in outdoor environments, addressing occlusion challenges and ensuring multi-view consistency.

Findings

CoCap outperforms existing methods in high occlusion scenarios.

It approaches ideal unconstrained planning outcomes.

Provides a real-time single-robot view search approach.

Abstract

Motion capture has become increasingly important, not only in computer animation but also in emerging fields like the virtual reality, bioinformatics, and humanoid training. Capturing outdoor environments offers extended horizon scenes but introduces challenges with occlusions and obstacles. Recent approaches using multi-drone systems to capture multiple actor scenes often fail to account for multi-view consistency and reasoning across cameras in cluttered environments. Coordinated motion Capture (CoCap), inspired by Conflict-Based Search (CBS), addresses this issue by coordinating view planning to ensure multi-view reasoning during conflicts. In scenarios with high occlusions and obstacles, where the likelihood of inter-robot collisions increases, CoCap demonstrates performance that approaches the ideal outcomes of unconstrained planning, outperforming existing sequential planning methods. Additionally, CoCap offers a single-robot view search approach for real-time applications in dense environments.