Various performance measures based on the ground truth and without ground truth exist to evaluate the quality of a developed tracking algorithm. The existing popular measures - average center location error (ACLE) and average tracking accuracy (ATA) based on ground truth, may sometimes create confusion to quantify the quality of a developed algorithm for tracking an object under some complex environments (e.g., scaled or oriented or both scaled and oriented object). In this article, we propose three new auxiliary performance measures based on ground truth information to evaluate the quality of a developed tracking algorithm under such complex environments. Moreover, one performance measure is developed by combining both two existing measures ACLE and ATA and three new proposed measures for better quantifying the developed tracking algorithm under such complex conditions. Some examples and experimental results conclude that the proposed measure is better than existing measures to quantify one developed algorithm for tracking objects under such complex environments.
翻译:基于地面真相和没有地面真相的各种业绩计量都存在,用以评估发达跟踪算法的质量;现有的流行计量法----平均中心位置误差(ACLE)和基于地面真相的平均跟踪准确性(ATA),有时可能造成混乱,无法量化在某些复杂环境中跟踪物体的发达算法的质量(例如,规模化或定向,或两者都有规模化和定向);在本条中,我们提议了三项基于地面真相信息的新的辅助性业绩计量,以评价在这种复杂环境中发达跟踪算法的质量;此外,一项业绩计量是结合现有两项措施(ACLE和ATA)和三项拟议新措施制定的,以便更好地量化在这种复杂条件下开发的跟踪算法;一些实例和实验结果结论认为,拟议计量法比现有计量在这种复杂环境中跟踪物体的发达算法更好。