Motion Focus Recognition in Fast-Moving Egocentric Video

• URL: http://arxiv.org/abs/2601.07154v1
• Date: Mon, 12 Jan 2026 02:53:51 GMT
• Title: Motion Focus Recognition in Fast-Moving Egocentric Video
• Authors: Daniel Hong, James Tribble, Hao Wang, Chaoyi Zhou, Ashish Bastola, Siyu Huang, Abolfazl Razi,
• Abstract summary: We propose a real-time motion focus recognition method that estimates the subject's intention from any egocentric video.<n> Evaluated on a collected egocentric action dataset, our method achieves real-time performance with manageable memory consumption.
• Score: 17.363244905814756
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: From Vision-Language-Action (VLA) systems to robotics, existing egocentric datasets primarily focus on action recognition tasks, while largely overlooking the inherent role of motion analysis in sports and other fast-movement scenarios. To bridge this gap, we propose a real-time motion focus recognition method that estimates the subject's locomotion intention from any egocentric video. Our approach leverages the foundation model for camera pose estimation and introduces system-level optimizations to enable efficient and scalable inference. Evaluated on a collected egocentric action dataset, our method achieves real-time performance with manageable memory consumption through a sliding batch inference strategy. This work makes motion-centric analysis practical for edge deployment and offers a complementary perspective to existing egocentric studies on sports and fast-movement activities.

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