Object tracking via the dynamic velocity Hough transform

P. Lappas, J. Carter, R. Damper
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引用次数: 10

Abstract

Motion tracking is an important task in computer vision. A new technique, the dynamic velocity Hough transform (DVHT), for tracking of parametric objects is described that extends the velocity Hough transform (VHT) to cater for arbitrary motion. Like the VHT, the new technique processes the whole image sequence, gathering global evidence of motion and structure. However, we do not assume constant linear velocity but rather allow arbitrary velocity. The method tries to find an optimal, smooth trajectory in the parameter space with maximum energy, where the latter incorporates both the structure of the moving object and the smoothness of motion. The constrained optimisation problem is solved using a temporal (time-delay) dynamic programming algorithm. Tracking in noise is much superior to the standard Hough transform.
利用动态速度霍夫变换对目标进行跟踪
运动跟踪是计算机视觉中的一个重要课题。提出了一种新的跟踪参数化目标的技术——动态速度霍夫变换(DVHT),它将速度霍夫变换(VHT)扩展到任意运动。与VHT一样,新技术处理整个图像序列,收集运动和结构的全局证据。然而,我们不假设恒定的线速度,而是允许任意速度。该方法试图在能量最大的参数空间中找到最优的光滑轨迹,其中最优轨迹结合了运动物体的结构和运动的平滑性。约束优化问题采用时间(时滞)动态规划算法求解。噪声下的跟踪比标准霍夫变换要好得多。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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