Abstract
Information fusion algorithms have been successful in many vision tasks such as stereo, motion estimation, registration and robot localization. Stereo and motion image analysis are intimately connected and can provide complementary information to obtain robust estimates of scene structure and motion. We present an information fusion based approach for multi-camera and multi-body structure and motion that combines bottom-up and top-down knowledge on scene structure and motion. The only assumption we make is that all scene motion consists of rigid motion. We present experimental results on synthetic and non-synthetic data sets, demonstrating excellent performance compared to binocular based state-of-the-art approaches for structure and motion.
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Andreopoulos, A., Tsotsos, J.K. (2007). Information Fusion for Multi-camera and Multi-body Structure and Motion. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds) Computer Vision – ACCV 2007. ACCV 2007. Lecture Notes in Computer Science, vol 4843. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76386-4_36
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DOI: https://doi.org/10.1007/978-3-540-76386-4_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76385-7
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