@conference {11904,
	title = {Contour migration: solving object ambiguity with shape-space visual guidance},
	booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems, 2002},
	volume = {1},
	year = {2002},
	month = {2002///},
	pages = {330- 335 vol.1 - 330- 335 vol.1},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {A fundamental problem in computer vision is the issue of shape ambiguity. Simply stated, a silhouette cannot uniquely identify an object or an object{\textquoteright}s classification since many unique objects can present identical occluding contours. This problem has no solution in the general case for a monocular vision system. This paper presents a method for disambiguating objects during silhouette matching using a visual servoing system. This method identifies the camera motion(s) that gives disambiguating views of the objects. These motions are identified through a new technique called contour migration. The occluding contour{\textquoteright}s shape is used to identify objects or object classes that are potential matches for that shape. A contour migration is then determined that disambiguates the possible matches by purposive viewpoint adjustment. The technique is demonstrated using an example set of objects.},
	keywords = {Artificial intelligence, camera motion, CAMERAS, Computer vision, contour migration, Databases, edge detection, Intelligent robots, Laboratories, Machine vision, object ambiguity, Object recognition, pattern matching, Robot vision systems, servomechanisms, SHAPE, shape matching, shape-space visual guidance, silhouette matching, visual servoing},
	isbn = {0-7803-7398-7},
	doi = {10.1109/IRDS.2002.1041410},
	author = {Abd-Almageed, Wael and Smith,C.E.}
}
@conference {12033,
	title = {3D motion representations in visual servo control},
	booktitle = {Proceedings of International Symposium on Computer Vision, 1995},
	year = {1995},
	month = {1995/11/21/23},
	pages = {61 - 66},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {A new approach to visual servoing and vision-guided robotics is introduced. This approach uses visual information for autonomous behavior. It amounts to using robust, global spatiotemporal representations easily extracted from the dynamic imagery. Specifically, the geometrical patterns of normal flows are used as the input to the servo mechanism. It is shown that the positions of these patterns are related to the three dimensional motion parameters. By locating the positions of these patterns, we can solve a variety of navigational problems with little computational effort},
	keywords = {3D motion representations, autonomous behavior, CAMERAS, computational effort, Computer vision, dynamic imagery, global spatiotemporal representations, image representation, Mobile robots, motion control, Navigation, navigational problems, Optical computing, Robot kinematics, Robot sensing systems, robot vision, Robot vision systems, Robotics and automation, servomechanisms, Servosystems, Spatiotemporal phenomena, vision-guided robotics, visual information, visual servo control, visual servoing},
	isbn = {0-8186-7190-4},
	doi = {10.1109/ISCV.1995.476978},
	author = {Ferm{\"u}ller, Cornelia and LoongFah Cheong and Aloimonos, J.}
}
