CAGD-based computer vision

Journal ArticleThree-dimensional model-based computer vision uses geometric models of objects and sensed data to recognize objects in a scene. Likewise, Computer Aided Geometric Design (CAGD) systems are used to interactively generate three-dimensional models during the design process. Despite this similarity, there has been a dichotomy between these fields. Recently, the unification of CAGD and vision systems has become the focus of research in the context of manufacturing automation. This paper explores the connection between CAGD and computer vision. A method for the automatic generation of recognition strategies based on the geometric properties of shape has been devised and implemented. This uses a novel technique developed for quantifying the following properties of features which compose models used in computer vision: robustness, completeness, consistency, cost, and uniqueness. By utilizing this information, the automatic synthesis of a specialized recognition scheme, called a Strategy Tree, is accomplished. Strategy Trees describe, in a systematic and robust manner, the search process used for recognition and localization of particular objects in the given scene. They consist of selected features which satisfy system constraints and Corroborating Evidence Subtrees which are used in the formation of hypotheses. Verification techniques, used to substantiate or refute these hypotheses, are explored. Experiments utilizing 3-D data are presented

CAGD-based computer vision

Journal ArticleThree-dimensional model-based computer vision uses geometric models of objects and sensed data to recognize objects in a scene. Likewise, Computer Aided Geometric Design (CAGD) systems are used to interactively generate three-dimensional models during the design process. Despite this similarity, there has been a dichotomy between these fields. Recently, the unification of CAGD and vision systems has become the focus of research in the context of manufacturing automation

CAGD-based computer vision

Journal ArticleAbstract-Three-dimensional model-based computer vision uses geometric models of objects and sensed data to recognize objects in a scene. Likewise, computer aided geometric design (CAGD) systems are used to interactively generate three-dimensional models during the design process. Despite this similarity, there has been a dichotomy between these fields. Recently, the unification of CAGD and vision systems has become the focus of research in the context of manufacturing automation

CAD-based 3-D object recognition

Journal ArticleWe propose an approach to 3-D object recognition using CAD-based geometry models for freeform surfaces. Geometry is modeled with rational B-splines by defining surface patches and then combining these into a volumetric model of the object. Characteristic features are then extracted from this model and subjected to a battery of tests to select an "optimal" subset of surface features which are robust with respect to the sensor being used (e.g. laser range finder versus passive stereo) and permit recognition of the object from any viewing position. These features are then organized into a "strategy tree" which defines the order in which the features are sought, and any corroboration required to justify issuing a hypotheses. We propose the use of geometric sensor data integration techniques as a means for formally selecting surface features on free-form objects in order to build recognition strategies. Previous work has dealt with polyhedra and generalized cylinders, whereas here we propose to apply the method to more general surfaces

Weighted feature selection criteria for visual servoing of a telerobot

Because of the continually changing environment of a space station, visual feedback is a vital element of a telerobotic system. A real time visual servoing system would allow a telerobot to track and manipulate randomly moving objects. Methodologies for the automatic selection of image features to be used to visually control the relative position between an eye-in-hand telerobot and a known object are devised. A weighted criteria function with both image recognition and control components is used to select the combination of image features which provides the best control. Simulation and experimental results of a PUMA robot arm visually tracking a randomly moving carburetor gasket with a visual update time of 70 milliseconds are discussed

A dynamic framwork for intelligent inspection

technical reportCAD Computer Aided Design typically involves the design manufacture and inspection of a me chanical part. The problem of reverse engineering is to take an existing mechanical part as the point of departure and to inspect or produce a design and perhaps a manufacturing process for the part. We propose to explore the feasibility of a new approach to inspection and reverse engineering applications. In particular we investigate the use of discrete event dynamic systems DEDS to guide and control the active exploration and sensing of mechanical parts for industrial inspection?? The proposed framework utilizes DEDS for constructing an observer for inspection purposes?

A dynamic framework for intelligent inspection

technical reportCAD (Computer Aided Design) typically involves the design, manufacture and inspection of a mechanical part. The problem of reverse engineering is to take an existing mechanical part as the point of departure and to inspect or produce a design, and perhaps a manufacturing process, for the part. We propose to explore the feasibility of a new approach to inspection and reverse engineering applications. In particular, we investigate t h e use of discrete event dynamic systems (DEDS) to guide and control the active exploration and sensing of mechanical parts for industrial inspection. The proposed framework utilizes DEDS for constructing an observer for inspection purposes

Industrial inspection and reverse engineering

Journal ArticleWe propose a new design for inspection and reverse engineering environments. We have designed and experimented with such an environment for capturing sense data of mechanical parts in an intelligent way. We construct a sensing ? CAD interface for the automatic reconstruction of parts from visual data. We briefly discuss the use of the dynamic recursive finite state machine (DRFSM) as a new discrete event dynamic system (DEDS) tool for controlling inspection and exploration. We also implement a graphical interface for designing DRFSM DEDS controllers

Feature-based reverse engineering of mechanical parts

Journal ArticleReverse engineering of mechanical parts requires extraction of information about an instance of a particular part sufficient to replicate the part using appropriate manufacturing techniques. This is important in a wide variety of situations, since functioning CAD models are often unavailable or unusable for parts which must be duplicated or modified. Computer vision techniques applied to 3-D data acquired using non-contact, three-dimensional position digitizers have the potential for significantly aiding the process. Serious challenges must be overcome, however, if sufficient accuracy is to be obtained and if models produced from sensed data are truly useful for manufacturing operations. This paper describes a prototype of a reverse engineering system which uses geometric representations natural to the manufacturing process. The system is interactive, which improves performance and allows for human entry of information that cannot be acquired from sensed data alone

An investigation into the use of physical modelling for the prediction of various feature types visible from different view points

This paper describes a general purpose flexible technique which uses physical modelling techniques for determining the features of a 3D object that are visible from any predefined view. Physical modelling techniques are used to determine which of many different types of features are visible from a complete set of viewpoints. The power of this technique lies in its ability to detect and parameterise object features, regardless of object complexity. Raytracing is used to simulate the physical process by which object features are visible so that surface properties (eg specularity, transparency) as well as object boundaries can be used in the recognition process. Using this technique occluding and non-occluding edge based features are extracted using image processing techniques and then parameterised. Features caused by specularity are also extracted and qualitative descriptions for these are defined