应用无源仿射模型的DPIV新算法

传统ＤＰＩＶ算法主要于基区域相关运算,此法由于概念简单,操作方便而被广泛接受,但是存在速度慢,错配点多等众所周知的缺点。此文根据ＤＰＩＶ的成像特点以及所研究对象的物理性质,提出了流场的无源仿射模型,结合修改得到的整体不流模型,形成了一种计算ＤＰＶＩ的新方法。     

A hybrid approach for stereo disparity computation

An alternative, hybrid approach for disparity estimation, based on the phase difference technique, is presented. The proposed technique combines the robustness of the matching method with the sub-pixel accuracy of the phase difference approach. A matching between the phases of the left and right signals is introduced in order to allow the phase difference method to work in a reduced disparity range. In this framework, a new criterion to detect signal singularities is proposed. The presented test cases show that the performance of the proposed technique in terms of accuracy and density of the disparity estimates has greatly improved. Received: 24 June 1997 / Accepted: 15 September 1998     

Optic flow estimation by a Hopfield neural network using geometrical constraints

Sparse optic flow maps are general enough to obtain useful information about camera motion. Usually, correspondences among features over an image sequence are estimated by radiometric similarity. When the camera moves under known conditions, global geometrical constraints can be introduced in order to obtain a more robust estimation of the optic flow. In this paper, a method is proposed for the computation of a robust sparse optic flow (OF) which integrates the geometrical constraints induced by camera motion to verify the correspondences obtained by radiometric-similarity-based techniques. A raw OF map is estimated by matching features by correlation. The verification of the resulting correspondences is formulated as an optimization problem that is implemented on a Hopfield neural network (HNN). Additional constraints imposed in the energy function permit us to achieve a subpixel accuracy in the image locations of matched features. Convergence of the HNN is reached in a small enough number of iterations to make the proposed method suitable for real-time processing. It is shown that the proposed method is also suitable for identifying independently moving objects in front of a moving vehicle. Received: 26 December 1995 / Accepted: 20 February 1997     

A method for inspecting industrial parts surfaces based on an optics model

A new method based on an optics model for highly reliable surface inspection of industrial parts has been developed. This method uses multiple images taken under different camera conditions. Phong's model is employed for surface reflection, and then the albedo and the reflection model parameters are estimated by the least squares method. The developed method has advantages over conventional binarization in that it can easily determine the threshold of product acceptability and cope with changes in light intensity when detecting defects.     

A model-driven approach for real-time road recognition

This article describes a method designed to detect and track road edges starting from images provided by an on-board monocular monochromic camera. Its implementation on specific hardware is also presented in the framework of the VELAC project. The method is based on four modules: (1) detection of the road edges in the image by a model-driven algorithm, which uses a statistical model of the lane sides which manages the occlusions or imperfections of the road marking – this model is initialized by an off-line training step; (2) localization of the vehicle in the lane in which it is travelling; (3) tracking to define a new search space of road edges for the next image; and (4) management of the lane numbers to determine the lane in which the vehicle is travelling. The algorithm is implemented in order to validate the method in a real-time context. Results obtained on marked and unmarked road images show the robustness and precision of the method. Received: 18 November 2000 / Accepted: 7 May 2001     

A real-time vision module for interactive perceptual agents

Abstract. Interactive robotics demands real-time visual information about the environment. Real-time vision processing, however, places a heavy load on the robot's limited resources, which must accommodate multiple other processes running simultaneously. This paper describes a vision module capable of providing real-time information from ten or more operators while maintaining at least a 20-Hz frame rate and leaving sufficient processor time for a robot's other capabilities. The vision module uses a probabilistic scheduling algorithm to ensure both timely information flow and a fast frame capture. In addition, it tightly integrates the vision operators with control of a pan-tilt-zoom camera. The vision module makes its information available to other modules in the robot architecture through a shared memory structure. The information provided by the vision module includes the operator information along with a time stamp indicating information relevance. Because of this design, our robots are able to react in a timely manner to a wide variety of visual events.     

TRIP: A Low-Cost Vision-Based Location System for Ubiquitous Computing

Sentient Computing provides computers with perception so that they can react and provide assistance to user activities. Physical spaces are made sentient when they are wired with networks of sensors capturing context data, which is communicated to computing devices spread through the environment. These devices interpret the information provided and react by performing the actions expected by the user. Among the types of context information provided by sensors, location has proven to be especially useful. Since location is an important context that changes whenever the user moves, a reliable location-tracking system is critical to many sentient applications. However, the sensor technologies used in indoor location tracking are expensive and complex to deploy, configure and maintain. These factors have prevented a wider adoption of Sentient Computing in our living and working spaces. This paper presents TRIP, a low-cost and easily deployable vision-based sensor technology addressing these issues. TRIP employs off-the-shelf hardware (low-cost CCD cameras and PCs) and printable 2-D circular markers for entity identification and location. The usability of TRIP is illustrated through the implementation of several sentient applications.     

A hybrid system approach for supporting digital libraries

A digital library (DL) consists of a database which contains library information and a user interface which provides a visual window for users to search relevant information stored in the database. Thus, an abstract structure of a digital library can be defined as a combination of a special purpose database and a user-friendly interface. This paper addresses one of the fundamental aspects of such a combination. This is the formal data structure for linking an object oriented database with hypermedia to support digital libraries. It is important to establish a formal structure for a digital library in order to efficiently maintain different types of library information. This article discusses how to build an object oriented hybrid system to support digital libraries. In particular, we focus on the discussion of a general purpose data model for digital libraries and the design of the corresponding hypermedia interface. The significant features of this research are, first, a formalized data model to define a digital library system structure; second, a practical approach to manage the global schema of a library system; and finally, a design strategy to integrate hypermedia with databases to support a wide range of application areas. Received: 15 December 1997 / Revised: June 1999     

Zoom tracking and its applications

We present a new active vision technique called zoom tracking. Zoom tracking is the continuous adjustment of a camera's focal length in order to keep a constant-sized image of an object moving along the camera's optical axis. Two methods for performing zoom tracking are presented: a closed-loop visual feedback algorithm based on optical flow, and use of depth information obtained from an autofocus camera's range sensor. We explore two uses of zoom tracking: recovery of depth information and improving the performance of scale-variant algorithms. We show that the image stability provided by zoom tracking improves the performance of algorithms that are scale variant, such as correlation-based trackers. While zoom tracking cannot totally compensate for an object's motion, due to the effect of perspective distortion, an analysis of this distortion provides a quantitative estimate of the performance of zoom tracking. Zoom tracking can be used to reconstruct a depth map of the tracked object. We show that under normal circumstances this reconstruction is much more accurate than depth from zooming, and works over a greater range than depth from axial motion while providing, in the worst case, only slightly less accurate results. Finally, we show how zoom tracking can also be used in time-to-contact calculations. Received: 15 February 2000 / Accepted: 19 June 2000     

A graph-theoretic model for optimizing queries involving methods

Traditional algorithms for optimizing the execution order of joins are no more valid when selections and projections involve methods and become very expensive operations. Selections and projections could be even more costly than joins such that they are pulled above joins, rather than pushed down in a query tree. In this paper, we take a fundamental look at how to approach query optimization from a top-down design perspective, rather than trying to force one model to fit into another. We present a graph model which is designed to characterize execution plans. Each edge and each vertex of the graph is assigned a weight to model execution plans. We also design algorithms that use these weights to optimize the execution order of operations. A cost model of these algorithms is developed. Experiments are conducted on the basis of this cost model. The results show that our algorithms are superior to similar work proposed in the literature. Received 20 April 1999 / Accepted 9 August 2000 Published online 20 April 2001     

Fast prototyping of parallel-vision applications using functional skeletons

We present a design methodology for real-time vision applications aiming at significantly reducing the design-implement-validate cycle time on dedicated parallel platforms. This methodology is based upon the concept of algorithmic skeletons, i.e., higher order program constructs encapsulating recurring forms of parallel computations and hiding their low-level implementation details. Parallel programs are built by simply selecting and composing instances of skeletons chosen in a predefined basis. A complete parallel programming environment was built to support the presented methodology. It comprises a library of vision-specific skeletons and a chain of tools capable of turning an architecture-independent skeletal specification of an application into an optimized, deadlock-free distributive executive for a wide range of parallel platforms. This skeleton basis was defined after a careful analysis of a large corpus of existing parallel vision applications. The source program is a purely functional specification of the algorithm in which the structure of a parallel application is expressed only as combination of a limited number of skeletons. This specification is compiled down to a parametric process graph, which is subsequently mapped onto the actual physical topology using a third-party CAD software. It can also be executed on any sequential platform to check the correctness of the parallel algorithm. The applicability of the proposed methodology and associated tools has been demonstrated by parallelizing several realistic real-time vision applications both on a multi-processor platform and a network of workstations. It is here illustrated with a complete road-tracking algorithm based upon white-line detection. This experiment showed a dramatic reduction in development times (hence the term fast prototyping), while keeping performances on par with those obtained with the handcrafted parallel version. Received: 22 July 1999 / Accepted: 9 November 2000     

A system to navigate a robot into a ship structure

Abstract. A prototype system has been built to navigate a walking robot into a ship structure. The 8-legged robot is equipped with an active stereo head. From the CAD-model of the ship good view points are selected, such that the head can look at locations with sufficient edge features, which are extracted automatically for each view. The pose of the robot is estimated from the features detected by two vision approaches. One approach searches in stereo images for junctions and measures the 3-D position. The other method uses monocular image and tracks 2-D edge features. Robust tracking is achieved with a method of edge projected integration of cues (EPIC). Two inclinometres are used to stabilise the head while the robot moves. The results of the final demonstration to navigate the robot within centimetre accuracy are given.     

Regularized CDWT optical flow applied to moving-target detection in IR imagery

A modified version of the CDWT optical flow algorithm developed by Magarey and Kingsbury is applied to the problem of moving-target detection in noisy infrared image sequences, in the case where the sensor is also moving. Frame differencing is used to detect pixel-size targets moving in strongly cluttered backgrounds. To compensate for sensor motion, prior to differencing, the background is registered spatially using the estimated motion field between the frames. Results of applying the method to three image sequences show that the target SNR is higher when the estimated motion field for the whole scene is explicitly regularized. A comparison with another optical flow algorithm is also presented.     

A database model for object dynamics

To effectively model complex applications in which constantly changing situations can be represented, a database system must be able to support the runtime specification of structural and behavioral nuances for objects on an individual or group basis. This paper introduces the role mechanism as an extension of object-oriented databases to support unanticipated behavioral oscillations for objects that may attain many types and share a single object identity. A role refers to the ability to represent object dynamics by seamlessly integrating idiosyncratic behavior, possibly in response to external events, with pre-existing object behavior specified at instance creation time. In this manner, the same object can simultaneously be an instance of different classes which symbolize the different roles that this object assumes. The role concept and its underlying linguistic scheme simplify the design requirements of complex applications that need to create and manipulate dynamic objects. Edited by D. McLeod / Received March 1994 / Accepted January 1996     

Perceptual correction for colour grading using sensor transformations and metameric data

We present a method of colour shade grading for industrial inspection of surfaces, the differences of which are at the threshold of human perception. This method converts the input data from the electronic sensor to the corresponding data as they would have been viewed using the human vision system. Then their differences are computed using a perceptually uniform colour space, thus approximating the way the human experts would grade the product. The transformation from the electronic sensor to the human sensor makes use of synthetic metameric data to determine the transformation parameters. The method has been tested using real data. Received: 17 November 1997 / Accepted: 15 September 1998     

A word extraction algorithm for machine-printed documents using a 3D neighborhood graph model

Automatic character recognition and image understanding of a given paper document are the main objectives of the computer vision field. For these problems, a basic step is to isolate characters and group words from these isolated characters. In this paper, we propose a new method for extracting characters from a mixed text/graphic machine-printed document and an algorithm for distinguishing words from the isolated characters. For extracting characters, we exploit several features (size, elongation, and density) of characters and propose a characteristic value for classification using the run-length frequency of the image component. In the context of word grouping, previous works have largely been concerned with words which are placed on a horizontal or vertical line. Our word grouping algorithm can group words which are on inclined lines, intersecting lines, and even curved lines. To do this, we introduce the 3D neighborhood graph model which is very useful and efficient for character classification and word grouping. In the 3D neighborhood graph model, each connected component of a text image segment is mapped onto 3D space according to the area of the bounding box and positional information from the document. We conducted tests with more than 20 English documents and more than ten oriental documents scanned from books, brochures, and magazines. Experimental results show that more than 95% of words are successfully extracted from general documents, even in very complicated oriental documents. Received August 3, 2001 / Accepted August 8, 2001