Registration between Point Cloud Streams and Sequential Bounding Boxes via Gradient Descent

• URL: http://arxiv.org/abs/2409.09312v1
• Date: Sat, 14 Sep 2024 05:16:34 GMT
• Title: Registration between Point Cloud Streams and Sequential Bounding Boxes via Gradient Descent
• Authors: Xuesong Li, Xinge Zhu, Yuexin Ma, Subhan Khan, Jose Guivant,
• Abstract summary: We propose an algorithm for registering sequential bounding boxes with point cloud streams. We show that the proposed method performs remarkably well with a 40% improvement in IoU.
• Score: 21.13347625031356
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this paper, we propose an algorithm for registering sequential bounding boxes with point cloud streams. Unlike popular point cloud registration techniques, the alignment of the point cloud and the bounding box can rely on the properties of the bounding box, such as size, shape, and temporal information, which provides substantial support and performance gains. Motivated by this, we propose a new approach to tackle this problem. Specifically, we model the registration process through an overall objective function that includes the final goal and all constraints. We then optimize the function using gradient descent. Our experiments show that the proposed method performs remarkably well with a 40\% improvement in IoU and demonstrates more robust registration between point cloud streams and sequential bounding boxes

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