烟草依赖者的注意偏向研究

Relapse has been a great challenge in clinical treatment and experimental studies of drug addiction. Recent studies suggest that psychological dependence may play a major role in addiction relapse, even more important than physiological dependence. Then a fundamental question arises: how to measure the psychological dependence? How to examine whether an addict has psychologically quitted when leaving drug rehabilitation centers? Self-report, a commonly used evaluation approach, is inevitably vulnerable to various cognitive influences, particularly in explicit tasks. Therefore, an objective index is necessary to evaluate the subliminal psychological drug dependence level. The objective of the current study was to develop such a psychological paradigm to probe the unaware attentional bias of in smoking addicts. Experiment 1 adapted the interocular suppression technique of binocular rivalry to study the attentional bias to cigarette pictures in smokers and age-matched nonsmoker. Results show that the smokers demonstrated similar attentional bias in both visible and unaware conditions, while non-smokers showed attentional bias only in the visible condition, and there was a significant interaction between experiment conditions and subject groups. These results provide compelling evidence for addiction-specific attentional bias in cigarette smokers, by minimizing the influence of confounding conscious factors. Furthermore, attentional bias of smokers in unawareness state was negatively correlated with their cigarette dependence levels, while their pre-test cigarette craving levels was positively correlated with their attnetional bias in the visible condition. This pair of correlations further demonstrated the advantages of unawareness state in disclosing stable dependence states, therefore supporting the effectiveness of the paradigm used in this study. Another interesting finding of Experiment 1 is that non-smokers also showed attentional bias in the visible condition. To exclude the possibility that the attentional bias found in experiment 1 was task-specific, experiment 2 adapted the most commonly-used visual dot probe task with smoking scenes as in relevant reference. The result in experiment 1 was well replicated, i.e., nonsmokers in experiment 2 also showed significant attentional bias to smoking-related stimuli, We interpenetrate this interesting finding as an effect of environmental influence, as the participants of the current study live in a highly smoking-exposed and smoking-encouraged environment, which is quite different with the participants of studies reported in the literature. A series of questionnaires and scales administered in the current study indeed show that most smokers smoked due to influence of the environment. They also acknowledged that smoking as an important media of social communication in China, and even considered that away from the smoking environment would effectively help them to quit. The current study also found that the disgust level towards cigarette pictures and smoking-related scenes of non-smokers was positively correlated with their attnentional bias in the visible condition of experiment 1. It is likely that in a highly smoking-encouraged environment, the remaining few on-smokers have severe disgust to cigarettes and smoking scenes; and their attentional bias might be caused by disgust avoidance. In conclusion, the current study represents the first study showing the existence of unaware attentional bias to smoking related stimuli in cigarette smokers by applying the interocular suppression paradigm, providing a reference to study of dependence of other drugs. The current study also found that our non-smoking participants also showed attentional bias to smoking related stimuli, which may be due to the possible influence of highly smoking-exposed environment of our participants.

The Effects of Visual Object Size in The Depth Perception in KM Mouse

Whether mice perceive the depth of space dependent on the visual size of object targets was explored when visual cues such as perspective and partial occlusion in space were excluded. A mouse was placed on a platform the height of which is adjustable. The platform located inside a box in which all other walls were dark exception its bottom through that light was projected as a sole visual cue. The visual object cue was composed of 4x4 grids to allow a mouse estimating the distance of the platform relative to the grids. Three sizes of grids reduced in a proportion of 2/3 and seven distances with an equal interval between the platform and the grids at the bottom were applied in the experiments. The duration of a mouse staying on the platform at each height was recorded when the different sizes of the grids were presented randomly to test whether the Judgment of the mouse for the depth of the platform from the bottom was affected by the size information of the visual target. The results from all conditions of three object sizes show that time of mice staying on the platform became longer with the increase in height. In distance of 20 similar to 30 cm, the mice did not use the size information of a target to judge the depth, while mainly used the information of binocular disparity. In distance less than 20 cm or more than 30 cm, however, especially in much higher distance 50 cm, 60 cm and 70 cm, the mice were able to use the size information to do so in order to compensate the lack of binocular disparity information from both eyes. Because the mice have only 1/3 of the visual field that is binocular. This behavioral paradigm established in the current study is a useful model and can be applied to the experiments using transgenic mouse as an animal model to investigate the relationships between behaviors and gene functions.

基于双目视觉的运动物体实时跟踪与测距

利用双目视觉信息系统实现三维空间中运动物体实时跟踪与测距。当运动目标超出视野范围时,可通过控制摄像机云台转动搜索目标。此外,还研究了在摄像头运动情况下,无需重新标定,即可实现运动物体测距的算法。这里,自适应背景建模法与CamShift算法用于实现运动物体的辨识与跟踪。实验结果证明了所提出的算法能够有效地追踪物体,并同时准确地测量它的三维位置。

基于双目重建不确定性的动态特征滤除

提出了一种基于双目视觉三维重建不确定性的环境动态特征滤除方法。针对利用立体视觉系统对机器人进行运动估计时,环境中的动态目标和环境静态背景与机器人的空间相对运动具有不一致性,将严重影响系统的精度的问题。根据动态目标与环境背景的空间运动不一致性,分析立体视觉三维重建的不确定性,利用重建的不确定性估计机器人与环境间的相对运动,通过随机一致性方法(RANSAC)滤除图像中的环境动态特征。仿真实验结果表明了本方法的可行性和有效性。

一种立体视觉系统高精度标定方法

本文介绍使用广角镜头成像的立体视觉系统的高精度标定方法,该方法利用平面单应矩阵约束估计像机内外参数的初值,优化过程中将三维重投影误差作为评价函数,结合遗传算法完成寻优过程,以保证估计出的像机参数是全局最优,避免陷入局部极小。实验结果表明:该方法的空间定位精度与传统方法相比有很大程度的提高。

基于模型的位姿估计中优化方法研究

介绍了基于模型的位姿估计中所使用的一些优化方法。为了提高位姿估计的精度,摄像机的标定参数必须足够精确,这就对标定过程的非线性优化算法提出了很高的要求,采用了一种新的优化目标函数,用来最小化控制点间的三维重建误差,从而使标定参数是全局最优;在双像机位姿估计中,引入了实时遗传算法进行全局搜索,加快了算法的收敛速度。最后的实验证明了这些方法的正确性并显示出这些方法在精度上比传统方法有了较大程度的提高。

目标位姿测量中的三维视觉方法

要测量出一组特征点分别在两个空间坐标系下的坐标 ,就可以求解两个空间目标间的位姿关系 .实现上述目标位姿测量方法的前提条件是要保证该组特征点在不同坐标系下 ,其位置关系相同 ,但计算误差的存在却破坏了这种固定的位置关系 .为此 ,提出了两种基于模型的三维视觉方法——基于模型的单目视觉和基于模型的双目视觉 ,前者从视觉计算的物理意义入手 ,通过简单的约束迭代求解实现模型约束 ;后者则将简单的约束最小二乘法和基于模型的单目视觉方法融合在一起来实现模型约束 .引入模型约束后 ,单目视觉方法可以达到很高的测量精度 .而基于模型的双目视觉较传统的无模型立体视觉方法位移精度提高有限 ,但姿态精度提高很多

面向月面探测作业的双目立体视觉测量及三维环境生成技术研究

星球漫游车技术是一项跨学科的综合性技术，它反映了一个国家整体科技水平和高技术产业的发展水平，对漫游车进行研究具有长远的战略意义。漫游车一般都工作在特殊的环境中，综合考虑功耗和有效载荷等问题，可以发现，非视觉传感器与视觉传感器相比在环境感知能力和综合性能方面都不甚理想，因此，基于视觉传感器的立体视觉定位也一直是各类漫游车用以感知环境所首选的技术。基于立体视觉可以构建相应的地面人机交互系统。该交互系统具有实现离线示教功能，通过虚拟现实和立体视觉技术实现虚拟漫游车在虚拟地形中行走，虚拟机械臂对虚拟物体进行研磨等功能。操作人员在虚拟环境中对月球车的各种运动进行验证以后，再将数据上传给真实的漫游车以实现真实的漫游和考察工作。因此，立体视觉系统性能的好坏将直接影响到漫游车的后续工作情况，它是漫游车自主导航和进行科学考察的基础，直接关系到漫游车的安全，是一项关键的技术。 本文的研究依托于中国科学院知识创新工程方向性项目“月球车月面探测作业支撑技术研究”，旨在探索立体视觉系统的实现及其与车载机械臂配合工作的问题。从理论和实践两个方面，对其中的若干关键技术，如双摄像机标定、对极几何恢复、图像校正、图像匹配、三维重建和车载机械臂视觉定位等进行了研究。主要研究成果如下： 1．提出一种基于坐标排序的标定特征点存储算法，使得两幅图像中的标定特征点能够快速准确的对应存储。基于径向一致约束（RAC）模型优化方法与直接光学法的优点，提出一种改进的光心确定方法，实验表明该方法有效地提高了Tsai两步法的标定与测量精度。以上两种方法为实现双摄像机的高精度标定奠定了基础。 2．在双摄像机的标定阶段，提出一种新的以三维重投影误差为优化目标的双摄像机两步标定算法，实验证明该方法的标定与测量精度要高于传统的基于二维重投影误差的方法。提出一种考虑多个畸变系数基于三维重投影误差的两步标定算法，实验证明该方法比只考虑一个畸变系数的Tsai两步法能够获得更高的标定与测量精度。研究了基于遗传算法和粒子群算法的双摄像机内、外参数的整体优化问题，实验证明可以获得比传统梯度下降法更高的标定与测量精度。以上改进方法可以使标定精度达到工程要求，并为后续的图像校正和三维测量奠定基础。 3．从简单背景和复杂背景两种情况对对极几何的离线恢复问题进行了研究。对于对极几何的离线恢复问题，提出了基于正确匹配标定特征点进行基础矩阵高精度估计的算法。该算法的特点是与标定共用同一组数据，其有效性得到了实验的验证。对于对极几何的在线恢复问题，基于摄像机成像几何原理证明了图像坐标系下存在的一种左右图像坐标间的约束关系，并设计了相应的稀疏匹配算法，采用两阶段鲁棒稀疏匹配算法对基础矩阵进行了高精度的估计，实现了对极几何的在线恢复。与传统方法相比，本文的方法速度更快，精度更高。 4．研究了标定与非标定图像的极线校正算法，利用上述改进方法求得的高精度的投影矩阵和基础矩阵，获得了令人满意的校正效果，为稠密匹配奠定了坚实的基础。研究并实现了四种稠密匹配算法，并进行了算法性能的比较。针对稠密匹配后的初始候选匹配点对，研究了三种误匹配的剔除方法。实验结果表明这些方法能够有效剔除误匹配点对，提高三维重建的效果。 5．研究了基于最小二乘法和立体成像几何法的三维重建算法，研究了一种集成上述多种改进算法的欧式三维重建算法。研究开发了三维重建软件，基于真实图像进行了欧式三维重建实验研究，取得了良好的重建效果。 6．以月球车为应用对象，研究了虚拟机械臂和车载机械臂的平面定位机理，构建了基于立体视觉的虚拟机械臂定位仿真平台。基于虚拟环境下验证好的数据，进行了月球车车载机械臂平面定位的实验，结果证明车载机械臂具有良好的视觉定位精度。