Multi-modal Tracking for Object based SLAM

Autor:	Singhal, Prateek, White, Ruffin, Christensen, Henrik
Rok vydání:	2016
Předmět:	Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	We present an on-line 3D visual object tracking framework for monocular cameras by incorporating spatial knowledge and uncertainty from semantic mapping along with high frequency measurements from visual odometry. Using a combination of vision and odometry that are tightly integrated we can increase the overall performance of object based tracking for semantic mapping. We present a framework for integration of the two data-sources into a coherent framework through information based fusion/arbitration. We demonstrate the framework in the context of OmniMapper[1] and present results on 6 challenging sequences over multiple objects compared to data obtained from a motion capture systems. We are able to achieve a mean error of 0.23m for per frame tracking showing 9% relative error less than state of the art tracker. Comment: Submitted to IROS 2016
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1603.04117 Zobrazit plný text záznamu View this record from Arxiv