An efficient and geometrically intuitive algorithm for reliably interpreting the image velocities of moving objects in 3-D is presented. It is well known that under a weak perspective the image motion of points on a plane can be characterized by an affine transformation. It is shown that the relative image motion of a nearby non-coplanar point and its projection on the plane is equivalent to motion parallax, and because it is independent of view rotations it is a reliable geometric cue to 3-D shape and viewer/object motion. The authors summarize why structure from motion algorithms are often very sensitive to errors in the measured image velocities and then show how to efficiently and reliably extract an incomplete qualitative solution. They also show how to augment this into a complete solution if additional constraints or views are available. A real-time example is presented in which the 3-D visual interpretation of hand gestures or a hand-held object is used as part of a man-machine interface. This is an alternative to the Polhemus coil instrumented Dataglove commonly used in sensing manual gestures.>

A robot vision system that automatically generates an object recognition strategy from a 3D model and recognizes the object using this strategy is presented. The appearance of an object from various viewpoints is described in terms of visible 2D features such as parallel lines and ellipses. Features are then ranked according to the number of viewpoints from which they are visible. The rank and feature extraction cost of each feature are used to generate a treelike strategy graph. This graph gives an efficient feature search order when the viewpoint is unknown, starting with commonly occurring features and ending with features specific to a certain viewpoint. The system searches for features in the order indicated by the graph. After detection, the system compares a lines representation generated from the 3D model with the image features to localize the object. Perspective projection is used in the localization process to obtain the precise position and attitude of the object, whereas orthographic projection is used in the strategy generation process to allow symbolic manipulation. Experimental results are given.>

A vision system is presented which automatically generates an object recognition strategy from a 3D model, and recognizes the object using this strategy. In this system, the appearances of an object from various viewpoints are described with visible 2D features, such as parallel lines and ellipses. Then, the features in the appearances are ranked according to the number of viewpoints from which they are visible. The rank and the feature extraction cost for each feature are considered to generate a tree-like strategy graph. It shows an efficient feature search order when the viewpoint is unknown, starting with commonly occurring features and ending with features specific to a certain viewpoint. The system searches for features in the order indicated by the graph. After detection, the system compares the line representation generated from the 3D model and the image features to localize the object.>

A visual navigation system for a robot working in a nuclear power plant is presented. Such a system should have two functions. One is to provide a rough environment map or directions towards a goal, such as turning left at the second corner. The other is to avoid obstacles and to find a passage for continuous movement of the robot. The operation of the system is divided into two stages. In the first stage, a multi-information local map (MIL map) describing information necessary for self-location measurement is created interactively from stereo images collected during remote-controlled navigation. The second stage is autonomous navigation. The robot moves autonomously by using the map with the aid of the second function of the system. The system consists of five subsystems: an environment teaching subsystem, to create the MIL map; a self-location measurement subsystem, to find the robot's own location; an obstacle detection subsystem; a path planning subsystem; and a path following subsystem. Experimental results from a mobile robot show the usefulness of the system.>