• egomotion estimation using assorted features

    نویسندگان :
    جزئیات بیشتر مقاله
    • تاریخ ارائه: 1392/07/24
    • تاریخ انتشار در تی پی بین: 1392/07/24
    • تعداد بازدید: 934
    • تعداد پرسش و پاسخ ها: 0
    • شماره تماس دبیرخانه رویداد: -
    we propose a novel minimal solver for recovering camera motion across two views of a calibrated stereo rig. the algorithm can handle any assorted combination of point and line features across the four images and facilitates a visual odometry pipeline that is enhanced by well-localized and reliably-tracked line features while retaining the well-known advantages of point features. the mathematical framework of our method is based on trifocal tensor geometry and a quaternion representation of rotation matrices. a simple polynomial system is developed from which camera motion parameters may be extracted more robustly in the presence of severe noise, as compared to the conventionally employed direct linear/subspace solutions. this is demonstrated with extensive experiments and comparisons against the 3-point and line-sfm algorithms.

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