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51
ASSERT: A Physician-in-the-loop Content-Based Retrieval System for HRCT Image Databases
, 1999
"... It is now recognized in many domains that content-based image retrieval (CBIR) from a database of images cannot be carried out by using completely automated approaches. One such domain is medical radiology for which the clinically useful information in an image typically consists of gray level varia ..."
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Cited by 84 (8 self)
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It is now recognized in many domains that content-based image retrieval (CBIR) from a database of images cannot be carried out by using completely automated approaches. One such domain is medical radiology for which the clinically useful information in an image typically consists of gray level variations in highly localized regions of the image. Currently, it is not possible to extract these regions by automatic image segmentation techniques. To address this problem, we have implemented a human-in-the-loop (a physician-in-the-loop, more specifically) approach in which the human delineates the pathology bearing regions (PBR) and a set of anatomical landmarks in the image when the image is entered into the database. From the regions thus marked, our approach applies low-level computer vision and image processing algorithms to extract attributes related to the variations in gray scale, texture, shape, etc. In addition, the system records attributes that capture relational information such...
Model-Based Object Recognition - A Survey of Recent Research
, 1994
"... We survey the main ideas behind recent research in model-based object recognition. The survey covers representations for models and images and the methods used to match them. Perceptual organization, the use of invariants, indexing schemes, and match verification are also reviewed. We conclude that ..."
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Cited by 68 (1 self)
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We survey the main ideas behind recent research in model-based object recognition. The survey covers representations for models and images and the methods used to match them. Perceptual organization, the use of invariants, indexing schemes, and match verification are also reviewed. We conclude that there is still much room for improvement in the scope, robustness, and efficiency of object recognition methods. We identify what we believe are the ways improvements will be achieved. ii Contents 1. Introduction .................................................................................................................................... 1 2. Representation ................................................................................................................................ 3 2.1 What makes a good shape representation? ............................................................................ 3 2.2 The choice of coordinate system ..........................................
Practical Reliable Bayesian Recognition of 2D and 3D Objects Using Implicit Polynomials and Algebraic Invariants
- IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1996
"... Patches of quadric curves and surfaces such as spheres, planes and cylinders have found widespread use in modeling and recognition of objects of interest in computer vision. In this paper, we treat use of more complex higher degree polynomial curves and surfaces of degree higher than two, which have ..."
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Cited by 52 (12 self)
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Patches of quadric curves and surfaces such as spheres, planes and cylinders have found widespread use in modeling and recognition of objects of interest in computer vision. In this paper, we treat use of more complex higher degree polynomial curves and surfaces of degree higher than two, which have many desirable properties for object recognition and position estimation, and attack the instability problem arising in their use with partial and noisy data. The scenario discussed in this paper is one where we have a set of objects that are modeled as implicit polynomial functions, or a set of representations of classes of objects with each object in a class modeled as an implicit polynomial function, stored in the database. Then, given partial data from one of the objects, we want to recognize the object (or the object class) or collect more data in order to get better parameter estimates for more reliable recognition. Two problems arising in this scenario are discussed in this paper : (...
3-D Computer Vision Using Structured Light: Design, Calibration and Implementation Issues
- Design, Calibration, and Implementation Issues,” Advances in Computers(43
, 1996
"... Structured Light (SL) sensing is a well established method of range acquisition for Computer Vision. This chapter provides thorough discussions of design issues, calibration methodologies and implementation schemes for SL sensors. The challenges for SL sensor development are described and a range of ..."
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Cited by 29 (2 self)
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Structured Light (SL) sensing is a well established method of range acquisition for Computer Vision. This chapter provides thorough discussions of design issues, calibration methodologies and implementation schemes for SL sensors. The challenges for SL sensor development are described and a range of approaches are surveyed. A novel SL sensor, PRIME, the PRofile Imaging ModulE has recently been developed and is used as a design example in the detailed discussions. KEYWORDS: Computer Vision,Range Image Acquisition, Structured Light Ranging, Real-Time Machine Vision, Sensor Calibration 0y This research is sponsored in part by grants awarded by the Japan Railways and the Office of Technology Development, U.S. Department of Energy. 1 Introduction Machine vision as a discipline and technology owes its creation, development and growth to digital computers. Without computers machine vision is not possible. The main objective of machine vision is to extract information useful for performin...
Task oriented vision
- In DARPA Image Understanding Workshop
, 1990
"... The copyright law of the United States (title 17, U.S. Code) governs the making of photocopies or other reproductions of copyrighted material. Any copying of this document without permission of its author may be prohibited by law. ..."
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Cited by 28 (2 self)
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The copyright law of the United States (title 17, U.S. Code) governs the making of photocopies or other reproductions of copyrighted material. Any copying of this document without permission of its author may be prohibited by law.
Graph Matching Using a Direct Classification of Node Attendance
- Pattern Recognition Journal
, 1996
"... An algorithm has been developed that finds isomorphisms between both graphs and subgraphs. The development is introduced in the object recognition problem domain. The method isolates matching subgraphs, finds a node-to-node mapping and reorders nodes thus permitting a direct comparison to be made be ..."
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Cited by 12 (4 self)
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An algorithm has been developed that finds isomorphisms between both graphs and subgraphs. The development is introduced in the object recognition problem domain. The method isolates matching subgraphs, finds a node-to-node mapping and reorders nodes thus permitting a direct comparison to be made between the resultant graphs. The algorithm is of polynomial order. It yields approximate results, maintaining a performance level for subgraph isomorphisms at or above 95% under a wide variety of conditions and with varying levels of noise. The performance on the full size comparisons associated with graph isomorphisms has been found to be 100/100, also under a variety of conditions. Performance metrics, methods of testing and results are presented. KEYWORDS: Direct Classification, Graph Isomorphism, Subgraph Isomorphism, Graph Matching, Object Recognition. 1 Introduction Object recognition is fundamentally a problem of subgraph isomorphism in that a model describes objects in their entiret...
3D Object Recognition and Pose with Relational Indexing
, 2000
"... This paper addresses the problem of recognizing 3D objects from 2D intensity images. It describes the object recognition system named RIO (relational indexing of objects), which contains a number of new techniques. RIO begins with an edge image obtained from a pair of intensity images taken with a s ..."
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Cited by 10 (0 self)
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This paper addresses the problem of recognizing 3D objects from 2D intensity images. It describes the object recognition system named RIO (relational indexing of objects), which contains a number of new techniques. RIO begins with an edge image obtained from a pair of intensity images taken with a single camera and two different lightings. From the edge image, a set of new high-level features and relationships are extracted, and a technique called relational indexing is used to efficiently recall 2D view-class object models that have similar relational descriptions from a potentially large database of models. Once a model has been hypothesized, pairs of 2D–3D corresponding features, including point pairs, line–segment pairs, and ellipse–circle pairs, are used in a new linear pose estimation framework to produce a hypothesized transformation from a 3D mesh model of the object to the image. The transformation is either accepted or rejected by a verification procedure that projects the 3D model wireframe to the image and computes a Hausdorff-like distance measure between the projected model and the edge image. The resultant object recognition system is able to recognize 3D objects having planar, cylindrical, and threaded surfaces in
Integrating Sensing, Task Planning and Execution for Robotic Assembly
- IEEE Trans. on Robotics and Automation
, 1996
"... Abstract-This paper deals with enhancing the level of autonomy in a robotic work cell. With that mission in mind, we present here an integrated framework for the sensing, the planning, and the execution aspects of assembly. In experimental demonstrations of this system on a PUMA762, we can now throw ..."
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Cited by 9 (0 self)
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Abstract-This paper deals with enhancing the level of autonomy in a robotic work cell. With that mission in mind, we present here an integrated framework for the sensing, the planning, and the execution aspects of assembly. In experimental demonstrations of this system on a PUMA762, we can now throw objects randomly into the workspace of the robot and the robot then automatically synthesizes a manipulation plan that includes the operations of sensing, grasping, and regrasping. Each operation is invoked only when it is deemed necessary for the successful execution of assembly. I.
