Binocular motion tracking by gaze fixation control and three-dimensional shape reconstruction
Binocular motion tracking by gaze fixation control and three-dimensional shape reconstruction
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DOI：
10.1163/156855303322554427
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发表时间：
2003-01
影响因子：
2
通讯作者：
Y. Satoh;Takayuki Okatani;K. Deguchi
中科院分区：
文献类型：
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作者：
Y. Satoh;Takayuki Okatani;K. Deguchi
对于人类视觉系统来说，连续地注视在三维（3-D）空间中移动的对象是一件容易的任务。在跟踪物体时，人类视觉似乎能够通过双目视觉理解其三维形状。我们推测，在人类视觉系统中，理解3-D形状的功能是必不可少的鲁棒跟踪的运动对象。为了验证这一猜想，我们构建了一个实验系统的双目视觉运动跟踪。该系统由一对主动云台摄像机和一个机器人手臂组成，摄像机模拟人眼，机器人手臂模拟人体颈部以下的运动。控制两个有源相机以便将它们的注视固定在物体表面上的特定点处。基于图像亮度的差异，从由相机拍摄的两个图像实时重建点周围的物体表面的形状。如果两个摄像头成功凝视物体表面上的一个点，就可以实时重建局部物体形状。同时，重建的形状用于保持注视的对象表面上的固定点，这使得能够鲁棒地跟踪对象。因此，这两个过程，三维形状的重建和保持固定点，必须相互连接，形成一个闭环。我们证明了这个框架的有效性，通过几个实验的视觉跟踪。
It is an easy task for the human visual system to gaze continuously at an object moving in three-dimensional (3-D) space. While tracking the object, human vision seems able to comprehend its 3-D shape with binocular vision. We conjecture that, in the human visual system, the function of comprehending the 3-D shape is essential for robust tracking of a moving object. In order to examine this conjecture, we constructed an experimental system of binocular vision for motion tracking. The system is composed of a pair of active pan-tilt cameras and a robot arm. The cameras are for simulating the two eyes of a human while the robot arm is for simulating the motion of the human body below the neck. The two active cameras are controlled so as to fix their gaze at a particular point on an object surface. The shape of the object surface around the point is reconstructed in real-time from the two images taken by the cameras based on the differences in the image brightness. If the two cameras successfully gaze at a single point on the object surface, it is possible to reconstruct the local object shape in real-time. At the same time, the reconstructed shape is used for keeping a fixation point on the object surface for gazing, which enables robust tracking of the object. Thus these two processes, reconstruction of the 3-D shape and maintaining the fixation point, must be mutually connected and form one closed loop. We demonstrate the effectiveness of this framework for visual tracking through several experiments.