This Letter proposes a novel state estimator called the visual odometry particle filter (VOPF) for improving accuracy of visual object trackers. For the VOPF, a novel visual odometry motion model that is better than the conventional constant velocity motion model is proposed. In addition, a new particle injection method to prevent sample impoverishment and the incorrect measurement detection method are proposed. Visual object tracking experiments using 30 visual object trackers demonstrate that the VOPF improves accuracy of the trackers and outperforms the conventional particle and Kalman filters using the CV motion model.

中文翻译：

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用于提高视觉对象跟踪器精度的视觉里程计粒子滤波器

这封信提出了一种称为视觉里程计粒子滤波器 (VOPF) 的新型状态估计器，用于提高视觉对象跟踪器的准确性。对于VOPF，提出了一种优于传统等速运动模型的新型视觉里程计运动模型。此外，还提出了一种新的粒子注入方法，以防止样品贫化和不正确的测量检测方法。使用 30 个视觉对象跟踪器的视觉对象跟踪实验表明，VOPF 提高了跟踪器的准确性，并且优于使用 CV 运动模型的传统粒子和卡尔曼滤波器。