Kinematics and Structure of a 3-D Rigid Object from a Sequence of Noise Images (Computer and Information Science)

这个项目所解决的问题是3的推理- 从噪声图像序列中提取运动物体的三维属性 的对象。 感兴趣的3D属性是 平移运动和位置，转换为全局比例因子， 旋转运动和位置，以及物体的结构 到一个全球的比例因子。 这项研究，高图像噪声水平 允许，也许多达20%的对象图像大小。 即使在高分辨率图像中也会出现这种噪声水平， 只要物体的图像相对于传感器较小 视野. 本提案中采用的方法是建立三维模型， 利用运动学原理进行刚体运动。 的 运动学方程、传播、平移和旋转是 以状态空间模型的形式来描述。 噪声特性 点或线形成测量模型。 鉴于这一点，或 在长帧序列上的线对应是可用的 (or我们的目标是开发递归和批处理 三维运动和结构估计技术 参数 业绩计量，如理论上 估计参数的可达到的下限将是 推导 两个摄像头问题的扩展也将是 尝试和算法开发将在这两个测试 合成的和真实的图像序列。

The problem addressed by this project is the inference of 3- D attributes of a moving object from a sequence of noisy images of the object. The 3-D attributes of interest are the translational motion and position, to a global scale factor, the rotational motion and position, and the object structure, again to a global scale factor. This research, high image noise levels are allowed, perhaps as much as 20% of the object image size. Such noise levels can occur even in high resolution imagery, whenever the image of the object is small relative to the sensor field of view. The approach taken in this proposal is to model the 3-D rigid body motion using the principles of kinematics. The kinematic equations propagationg translation and rotation are written in the form of a state space model. The noisy feature points or lines form the measurement model. Given that point or line correspondences over a long sequence of frames are available (or established) our goal to develop recursive and batch techniques for the estimation of 3-D motion and structure parameters. Performance measures such as the theoretically attainable lower bounds for the estimated parameters will be derived. Extensions to the two camera problem will also be attempted and algorithms developed will be tested on both synthetic and real image sequences.