基于时间上下文跟踪学习检测的指尖跟踪方法

针对在基于视频的空中签名认证系统中,现有方法无法满足指尖跟踪的准确性、实时性和鲁棒性要求的问题,在对比研究目前常用的多种跟踪方法的基础上,提出一种基于时间上下文的跟踪-学习-检测(TLD)方法。在原始TLD算法的基础上引入时间上下文信息,即相邻两帧间指尖运动具有连续性的先验知识,自适应地缩小检测和跟踪的搜索范围,以提高跟踪的速度。对12组公开的1组自录的视频序列的实验结果表明,改进后的TLD算法能够准确地跟踪指尖,并且跟踪速度达到43帧/秒;与原始TLD跟踪算法相比,准确率提高了15%,跟踪速度至少提高1倍,达到了指尖跟踪的准确性、实时性和鲁棒性要求。

Fingertip tracking method based on temporal context tracking-learning-detection

In the video based in-air signature verification system, the existed methods cannot meet the requirement of accuracy, real time, robustness for fingertip tracking. To solve this problem, the Tracking-Learning-Detection (TLD) method based on temporal context was proposed. Based on the original TLD algorithm, the temporal context massage, namely the prior knowledge that the movement of fingertip is continuity in two adjacent frames, was introduced to narrow the search range of detection and tracking adaptively, thereby improving tracking speed. The experimental results on 12 public and 1 self-made video sequences show that the improved TLD algorithm can accurately track fingers, and tracking speed can reach 43 frames per secend. Compared with the original TLD tracking algorithm, the accuracy was increased by 15% and the tracking speed was increased more than 100%, which make the proposed method meet the real-time requirements for fingertip tracking.