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

2024-12-30

AI Summary

In outdoor motion capture with high occlusion and multiple obstacles, multi-UAV collaboration suffers from inconsistent viewpoint selection and path conflicts. Method: This paper proposes a conflict-based search (CBS)-inspired cooperative view-planning framework—the first to adapt the CBS paradigm to multi-view motion capture—comprising a real-time single-UAV viewpoint search algorithm that jointly integrates multi-agent path planning, multi-view geometric constraints, and online conflict detection/resolution. Contribution/Results: The method achieves near-optimal performance under severe occlusion, closely approximating unconstrained ideal planning; it significantly outperforms conventional sequential approaches in accuracy while enabling real-time, dense UAV deployment. To our knowledge, it is the first solution for complex outdoor multi-actor motion capture that simultaneously ensures view consistency, geometric accuracy, and real-time responsiveness.

Technology Category

• Computer Vision: Motion & Tracking
• Intelligent Robots: Motion and Path Planning
• Humans and AI: Planning and Decision Support for Human-Machine Teams

Application Category

• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking

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.

Problem

• Multi-drone systems
• Occlusion handling
• Synchronized motion capture

Innovation

• CoCap
• Multi-Drone Synchronization
• Real-time Viewpoint Search