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基于FPGA与投影算法的快速眼动跟踪系统实现 被引量:4

Rapid Eye Movement Tracking System Based on FPGA and Projection Algorithm
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摘要 以视觉刺激的方式给被测者眼动任务,并使用高速摄像系统来跟踪被测对象的眼动轨迹,可以获知其心理行为,在心理研究领域具有非常重要的作用。介绍了一种基于FPGA硬件和投影算法的眼动跟踪系统,通过LUPA300高速CMOS图像传感器采集眼动图像,利用FPGA实现投影算法从连续的视频帧中获取人眼瞳孔与反射斑的坐标。为提高跟踪的准确程度,包括二值化与数学形态学腐蚀膨胀运算被用于预处理,最终实现了快速瞳孔与反射斑的定位。结果表明,FPGA执行快速投影跟踪算法,可以获得可靠的跟踪准确性,在跟踪算法中利用FPGA对图像首先进行二值化及腐蚀膨胀预处理,可以达到更好的效果。系统构成简单,实现了实时跟踪,结果准确,为高速眼动跟踪提供了一种新的有效实现方法。 Assigning an eye task with visual stimulation and tracking the eye movement is a channel to acquire the examinees'psychological behaviors, which plays a critical part in the fields of psychological research. In this study, an eye-tracking system based on FPGA hardware and projection algorithm was proposed, which captures video via LUPA300 high-speed CMOS and obtains the motion of eye pupil and bright spot through the continuous video frames by using a FPGA implemented projection algorithm. To obtain a reliable tracking accuracy, a binarization and mathematical morphology operation (corrosion and expansion) were adopted as a pre-procession step. The results showed that FPGA can implement projection algorithm to track eye motion with high speed, and the binarization and corrosion expansion pretreatment can improve the tracking accuracy effectively. The system is easy to achieve the real time tracking, and provides a new method for eye movement tracking at high speed.
出处 《四川大学学报(工程科学版)》 EI CAS CSCD 北大核心 2016年第3期100-106,共7页 Journal of Sichuan University (Engineering Science Edition)
基金 国家自然科学基金仪器专项资助项目(81227002)
关键词 眼动 FPGA 运动跟踪 投影算法 腐蚀 膨胀 eye movement FPGA motion tracking projection algorithm corrosion expansion
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  • 1Najemnik J,Geisler W S.Optimal eye movement strategies in visual search[J].Nature,2005,434(7031):387-391.
  • 2Noureddin B,Lawrence P D,Birch G E.Time-frequency analysis of eye blinks and saccades in EOG for EEG ar- tifact removal[C]//Proceedings of 20073rd International IEEE/EMBS Conference on Neural Engineering.Hawaii:IEEE,2007:564-567.
  • 3Noureddin B,Lawrence P D,Birch G E.Online removal of eye movement and blink EEG artifacts using a high- speed eye tracker[J].IEEE Transactions on Biomedical Engineering,2012,59(8):2103-2110.
  • 4Nouar O D,Ali G,Raphael C.Improved object tracking with Camshift algorithm[C]//Proceedings of 2006 IEEE International Conference on Acoustics,Speech and Signal Processing.Toulouse:IEEE,2006,2:657-660.
  • 5Zhang Zaifeng.The system implementation of Iris recogni- tion algorithm research machine.Lanzhou[D]:Lanzhou U- niversity,2009.
  • 6Allen J G,Xu R Y D,Jin J S.Object tracking using camshift algorithm and multiple quantized feature spaces[C]//Proceedings of the Pan-Sydney Area Workshop on Visual Information Processing.Darlinghurst,Australia:ACM,2004:3-7.
  • 7[美]冈萨雷斯,伍兹.数字图像处理的Matlab实现[M].阮秋琦,译.2版.北京:清华大学出版社,2013.
  • 8Shan Shiguang.Several key problems in face recognition research[D].Beijing:Graduate school of Chinese academy of sciences ( Institute of computing technology),2004.
  • 9Deng Lei.Using FPGA to realize image format conver- sion[J].Journal of Sichuan University:Natural Science E- dition,2002,39(l):158-160.
  • 10邓蕾.用FPGA实现图象格式的转换[J].四川大学学报(自然科学版),2002,39(1):158-160. 被引量:1

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