-
[show abstract]
[hide abstract]
ABSTRACT: A CMOS log-polar or foveated image sensor for use in mobile
robotic and machine vision applications has been designed, fabricated,
and tested. The sensor benefits from a high degree of integration,
minimal power consumption, and ease of manufacture due to the use of a
standard 1.2 μm ASIC CMOS process. The sensor is composed of two
distinct CMOS imager arrays which together solve the problem of
obtaining good image resolution over a wide field of view. With
resolution sensing is accomplished with a 40×40 array of
individual pixels each measuring 9.6 μm on a side. A wide field of
view is provided by an array of 64×16 pixels arranged on a
log-polar grid. The maximum measured dynamic range for the fabricated
log-polar array is 46 dB, while the lowest observed fixed-pattern noise
is 0.5% of saturation. Combined power consumption of both arrays is
under 2 mW when operating from a single 5-V supply at a frame rate of 30
frames/s
IEEE Journal of Solid-State Circuits 09/1997; · 3.23 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: A novel approach to 3D part segmentation is presented. Beginning
with range data of a 3D object, we simulate the charge density
distribution over an object's surface which has been tessellated by a
triangular mesh. We then locate the object part boundary at deep surface
concavities by tracing local charge density minima. Finally, we
decompose the object into parts at the part boundary points
Pattern Recognition, 1996., Proceedings of the 13th International Conference on; 09/1996
-
[show abstract]
[hide abstract]
ABSTRACT: For pt.I. see ibid., p.259-74. This paper presents the results of
experiments performed to validate the computer retina model presented in
part I. Experiments commonly performed by electrophysiologists on
biological retinas are simulated and the computer retina outputs
compared with published recordings of cells in biological (principally
primate) retinas. Experiments with more complex stimuli further reveal
how the computer retina enhances spatio-temporal contrast information
and adapts to a wide range of illumination levels much like the primate
retina
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) 05/1996; · 3.08 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: For pt.I. see ibid., p.259-74. This paper presents the results of experiments performed to validate the computer retina model presented in part I. Experiments commonly performed by electrophysiologists on biological retinas are simulated and the computer retina outputs compared with published recordings of cells in biological (principally primate) retinas. Experiments with more complex stimuli further reveal how the computer retina enhances spatio-temporal contrast information and adapts to a wide range of illumination levels much like the primate retina.
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) 02/1996; 26(2):275-89. · 3.08 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: At the retinal level, the strategies utilized by biological visual systems allow them to outperform machine vision systems, serving to motivate the design of electronic or "smart" sensors based on similar principles. Design of such sensors in silicon first requires a model of retinal information processing which captures the essential features exhibited by biological retinas. In this paper, a simple retinal model is presented, which qualitatively accounts for the achromatic information processing in the primate cone system. The computer retina model exhibits many of the properties found in biological retinas such as data reduction through nonuniform sampling, adaptation to a large dynamic range of illumination levels, variation of visual acuity with illumination level, and enhancement of spatiotemporal contrast information. The main emphasis of the model presented here is to demonstrate how different adaptation mechanisms play a role in extending the operating range of the primate retina.
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) 02/1996; 26(2):259-74. · 3.08 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: We propose a novel approach to 3D part segmentation. From physics
it is known that on the surface of a charged conductor, charge tends to
accumulate at a sharp convexity and vanishes at a sharp concavity. Thus
object part boundaries, which are usually denoted by a sharp surface
concavity, can be detected by locating surface points exhibiting focal
charge minima. Beginning with multiview range data of a 3D object, we
simulate the electrical charge distribution over an object's surface
which has been tessellated by a triangular mesh. We detect the deep
surface concavities by tracing local charge density minima and then
decompose the object into parts at these points
Computer Vision, 1995. Proceedings., International Symposium on; 12/1995
-
[show abstract]
[hide abstract]
ABSTRACT: This paper discusses two components of a Robot Eye intended as an active vision system to be mounted on a mobile robot. The first component is a foveated vision sensor which is based on an overlapping receptive field model for data reduction. We present the adapted scan-line algorithm used to compute so-called retinal images and a description of the implementation of the system on a network of DSP's. The second component computes salient points in the foveated image and is motivated by the biological processes which guide primate gaze fixation. The model of attention and its real-time implementation are described. Experimental results obtained with these algorithms are also presented
Computer Architectures for Machine Perception, 1995. Proceedings. CAMP '95; 10/1995
-
[show abstract]
[hide abstract]
ABSTRACT: Biological creatures apparently execute many tasks in the world by
using a combination of routine skills, without doing any extensive
reasoning. In recent years researchers have used this as a guide to
formulate behavioral architectures for robot control. The authors have
adopted the teleo-reactive (TR) formalism introduced by Nils Nilsson
(1994) for their behavioral architecture. The formalism is a programming
methodology for situated agents. The authors have implemented and
expanded the TR formalism so that the program interpreter executes the
computations in parallel. This is necessary in order for a situated
agent to interact with its environment in real-time. Further extensions
to the TR formalism include condition and action expressions, the
flexibility of controlling how and when conditions are evaluated and the
ability to control the computation frequency rate of condition
processes. The authors' formalism is called TR+. A TR+ program was used
to navigate a robot in the authors' lab in real-time
Electrical and Computer Engineering, 1995. Canadian Conference on; 10/1995
-
[show abstract]
[hide abstract]
ABSTRACT: We present a machine vision system in which segmentation is computed in conjunction with a structural description of objects in the scene. It is assumed that contrast edges capture all relevant object information. The principles which dictate how edge features are grouped to infer objects are based upon detecting SYMMETRICAL ENCLOSING edge configurations. These are detected using ANNULAR OPERATORS applied at multiple scales to edge data which have been extracted at multiple scales from a gray level image. The subsequent grouping of symmetry points results in a set of PARTS which make it possible to identify the LOCATION of objects within an image. These parts are used as a basis for constructing coarse graph-based DESCRIPTORS for the PERCEPTUALLY SIGNIFICANT objects found in the scene. Results are presented to illustrate the method's performance on several images
Computer Vision, 1995. Proceedings., Fifth International Conference on; 07/1995
-
[show abstract]
[hide abstract]
ABSTRACT: It is essential that autonomous robots be able to locate and
identify objects in their environment. A novel approach for visually
extracting such object information from images is presented. Annular
operators are used to identify existing symmetric relationships between
sets of edge elements. Operators are applied at multiple scales to edge
data which have been extracted at multiple scales from a gray-scale
image. From the resulting symmetry points, the authors identify a set of
object parts in the scene. These are used as the basis for constructing
coarse graph-based object descriptors. Preliminary results are presented
to illustrate the approach using natural image data
Robotics and Automation, 1995. Proceedings., 1995 IEEE International Conference on; 06/1995
-
[show abstract]
[hide abstract]
ABSTRACT: We describe the design and implementation of a CMOS foveated image
sensor for use in mobile robotic and machine vision applications. The
sensor is biologically motivated and performs a spatial image
transformation from Cartesian to log-polar coordinates. As opposed to
traditional approaches, the sensor benefits from a high degree of
integration, minimal power consumption and ease of manufacture due to
the use of a standard 1.2 μm ASIC CMOS process. The prototype imager
operates at 28 frames/sec when interfaced to a PC
Custom Integrated Circuits Conference, 1995., Proceedings of the IEEE 1995; 06/1995
-
[show abstract]
[hide abstract]
ABSTRACT: A major requirement of an automated, real-time, computer vision-based cell tracking system is an efficient method for segmenting cell images. The usual segmentation algorithms proposed in the literature exhibit weak performance on live unstained cell images, which can be characterized as being of low contrast, intensity-variant, and unevenly illuminated. We propose a two-stage segmentation strategy which involves: 1) extracting an approximate region containing the cell and part of the background near the cell, and 2) segmenting the cell from the background within this region. The approach effectively reduces the influence of peripheral background intensities and texture on the extraction of a cell region. The experimental results show that this approach for segmenting cell images is both fast and robust.
IEEE Transactions on Biomedical Engineering 02/1995; 42(1):1-12. · 2.28 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: We have studied the problem of deriving object part approximations
by a new set of distinct volumetric shape types called parametric geons
from multiview and single-view range data. This is accomplished by
fitting the models to range data of single-part objects and then
classifying the fitting residuals. We investigate how the number of
object views can affect the ultimate shape approximation. Experimental
results show that qualitative shape information can be recovered using
data taken from single general views, and that multiview data
significantly improve the accuracy of the quantitative model information
Pattern Recognition, 1994. Vol. 1 - Conference A: Computer Vision & Image Processing., Proceedings of the 12th IAPR International Conference on; 11/1994
-
[show abstract]
[hide abstract]
ABSTRACT: Focuses on approximating object part shapes by distinctive types
of volumetric primitives. Shape approximation is accomplished by fitting
volumetric models called `parametric geons' to multiview range data of
single-part objects and classifying the fitting residuals. Parametric
geons are seven qualitative shape types defined by parameterized
equations which control the size and degree of tapering and bending.
Model fitting is performed by minimizing an objective function which
measures the similarity in both size and shape between models and
objects. Multiple view data, global shape constraints and global
optimization are employed to obtain unique models and to compensate for
noise and minor variations in object shape. This approach has been
studied in experiments with both synthetic 3D data and actual
rangefinder data of perfect and imperfect geon-like objects
Computer Vision and Pattern Recognition, 1994. Proceedings CVPR '94., 1994 IEEE Computer Society Conference on; 07/1994
-
[show abstract]
[hide abstract]
ABSTRACT: The problems of segmenting a noisy intensity image and tracking a nonrigid object in the plane are discussed. In evaluating these problems, a technique based on an active contour model commonly called a snake is examined. The technique is applied to cell locomotion and tracking studies. The snake permits both the segmentation and tracking problems to be simultaneously solved in constrained cases. A detailed analysis of the snake model, emphasizing its limitations and shortcomings, is presented, and improvements to the original description of the model are proposed. Problems of convergence of the optimization scheme are considered. In particular, an improved terminating criterion for the optimization scheme that is based on topographic features of the graph of the intensity image is proposed. Hierarchical filtering methods, as well as a continuation method based on a discrete sale-space representation, are discussed. Results for both segmentation and tracking are presented. Possible failures of the method are discussed
IEEE Transactions on Pattern Analysis and Machine Intelligence 07/1993; 15(6):617-634. · 4.91 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: Primal access recognition of visual objects (PARVO), a computer vision system that addresses the problem of fast and generic recognition of unexpected 3D objects from single 2D views, is considered. Recently, recognition by components (RBC), which is a new human image understanding theory, based on some psychological results, has been proposed as an explanation of how PARVO works. However, no systematic computational evaluation of its many aspects has yet been reported. The PARVO system discussed is a first step toward this goal, since its design respects and makes explicit the main assumptions of the proposed theory. It analyzes single-view 2D line drawings of 3D objects typical of the ones used in human image understanding studies. It is designed to handle partially occluded objects of different shape and dimension in various spatial orientations and locations in the image plane. The system is shown to successfully compute generic descriptions and then recognize many common man-made objects
IEEE Transactions on Pattern Analysis and Machine Intelligence 02/1993; 15(1):19-36. · 4.91 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: A method for shape description of planar objects that integrates both region and boundary features is presented. The method is an implementation of a 2D dynamic grassfire that relies on a distance surface on which elastic contours minimize an energy function. The method is based on an active contour model. Numerous implementation aspects of the shape description method were optimized. A Euclidean metric was used for optimal accuracy, and the active contour model permits bypassing some of the discretization limitations inherent in using a digital grid. Noise filtering was performed on the basis of both contour feature measures and region measures, that is, curvature extremum significance and ridge support, respectively, to obtain robust shape descriptors. Other improvements and variations of the algorithmic implementation are proposed
IEEE Transactions on Pattern Analysis and Machine Intelligence 02/1992; 14(1):56-75. · 4.91 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: The authors describe the geometrical criteria which define viewpoint-invariant features to be extracted from 2-D line drawings of 3-D objects. They also discuss the extraction of these features, which forms the initial stage of a generic object recognition system, the Primal Access Recognition of Visual Objects (PARVO) system. In this system, part-based qualitative descriptions are built and matched to coarse 3-D object models for recognition. The segmentation and labeling of the constituent parts of an object rely on the 3-D properties inferred from the presence of its 2-D features. The original motivation for PARVO its recognition by components, a theory of human image understanding from the field of psychology. Definitions of the geometrical criteria defining the viewpoint-invariant features are introduced. Examples of results obtained by applying these criteria to a typical line drawing are shown
Pattern Recognition, 1990. Proceedings., 10th International Conference on; 07/1990
-
[show abstract]
[hide abstract]
ABSTRACT: PARVO, a computer vision system that addresses the problems of
fast and generic recognition of unexpected 3D objects from single 2D
views, is introduced. Recently, RBC (recognition by components), a new
human image understanding theory, has been proposed on the basis of the
results of various psychological studies. However, no systematic
computational evaluation of its many aspects has been reported yet. The
object recognition system the authors have built is a first step toward
this goal, since its design respects and makes explicit the main
assumptions of the proposed theory. It analyzes single-view 2D line
drawings of 3D objects typical of the ones used in human image
understanding studies. The main issues related to generic object
recognition are discussed, original algorithms and techniques specific
to the author's systems are described, and results of the different
processing stages of the system are presented
Interpretation of 3D Scenes, 1989. Proceedings., Workshop on; 12/1989
-
[show abstract]
[hide abstract]
ABSTRACT: An approach to the computation of a representation of objects with
a planar and curved faces using discontinuity features in range images
is presented. Edge maps are computed from real laser triangulation
images using local operators and shadow analysis, and then structured
into an edge-junction graph embedding and quantitative information. This
is achieved by appealing to certain concepts of line-drawing analysis
adapted to the three-dimensional nature of range imaging. The
edge-oriented method is primarily useful for objects that are
well-described by their edges. The main advantage of edge-based
descriptions is that no fixed surface primitives are assumed. On the
other hand, this scheme can only represent objects without any surface
crease edges (such as a sphere) by viewpoint-dependent limb edges. This
information may be insufficient for the ensuing high-level task. Thus, a
generalization of the description format might include a surface
analysis to provide a richer representation
Computer Vision and Pattern Recognition, 1989. Proceedings CVPR '89., IEEE Computer Society Conference on; 07/1989
