NSF Young Investigator

人类用自己的身体来相互沟通。 这种沟通的大部分是由视觉介导的，然而视觉目前还不是。 用于人机界面。 如果我们能模仿 性质 和 获得良好的人机交互 视觉沟通，我们可以建立方便，便携和强大的界面。 这 科技将对娱乐，电讯，手提电脑及保安等行业作出重大贡献。 佩罗纳医生会研究 用于跟踪和识别，旨在建立人与计算机之间的视觉界面。 他的研究将集中在三个系统：面部，手部和四肢，包括头部和身体姿势。 为了获取肢体和手传递的信息， 有必要将它们定位在可能杂乱的 图像和 然后重建它们在空间和时间上的结构。必须检测面部，计算其3D方向， 其特点是位于 并测量其变形。 Perona博士的研究将相应地集中在运动流和3D运动的场景分割，运动学的3D运动的递归估计， 链 具有部分 已知 运动学 从单目和立体的角度来看， 图像，检测复杂的物体（手，脸）， 场景，非刚性运动的表示和估计。

Humans use their body to communicate with each other. Much of this communication is mediated by vision, however vision is not currently used in human-to-machine interfaces. If we could imitate nature and obtain good human-to-machine visual communication we could build convenient, portable and powerful interfaces. This technology would contribute immensely to industries such as entertainment, telecommunications, portable computing and security. Dr. Perona will study techniques for tracking and recognition aimed at building visual interfaces between humans and computers. His research will concentrate on three systems: the face, the hands, and the limbs, including head and body posture. In order to access the information conveyed by the limbs and the hand it is first necessary to locate them in potentially cluttered images and then to reconstruct their configuration in space and time. The face has to be detected, its 3D orientation computed, its features located and its deformation measured. Dr. Perona's research will accordingly concentrate on scene segmentation from motion flow and 3D motion, recursive estimation of the 3D motion of kinematic chains with partially known kinematics from monocular and stereoscopic sequences of perspective images, detection of complex objects (hands, face) in cluttered scenes, representation and estimation of nonrigid motions.