WorldCat Identities

Huttenlocher, Daniel P.

Overview
Works: 29 works in 68 publications in 1 language and 465 library holdings
Roles: Author, Other
Classifications: TA1632, 621.367
Publication Timeline
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Most widely held works by Daniel P Huttenlocher
Object recognition by computer : the role of geometric constraints by William Eric Leifur Grimson( Book )

6 editions published in 1990 in English and held by 376 WorldCat member libraries worldwide

Recognizing solid objects by alignment with an image by Daniel P Huttenlocher( Book )

3 editions published in 1989 in English and held by 6 WorldCat member libraries worldwide

We have implemented a recognition system that uses this transformation method to determine possible alignments of a model with an image. Each of these hypothesized matches is verified by comparing the entire edge contours of the aligned object with the image edges. Using the entire edge contours for verification, rather than a few local feature points, reduces the chance of finding false matches. The system has been tested on partly occluded objects in highly cluttered scenes."
On planar point matching under affine transformation by John E Hopcroft( Book )

4 editions published in 1989 in English and held by 6 WorldCat member libraries worldwide

In general, the number of transformations will be much smaller, so we have developed an output sensitive algorithm that runs in time O(n[superscrpit 2]log n + tm log n), where [formulas], and t depends on the number of transformations. The method relies on the affine properties that intersection points and length ratios along a line are preserved."
On dynamic Voronoi diagrams and the minimum Hausdorff distance for point sets under Euclidean motion in the plane by Daniel P Huttenlocher( Book )

3 editions published in 1992 in English and held by 5 WorldCat member libraries worldwide

Abstract: "We show that the dynamic Voronoi diagram of k sets of points in the plane, where each set consists of n points moving rigidly, has complexity O(n²k²[lambda subscript s](k)) for some fixed s, where [lambda subscript s](n) is the maximum length of a (n, s) Davenport-Schinzel sequence. This improves the result of Aonuma et. al., who show an upper bound of O(n³k⁴log*k) for the complexity of such Voronoi diagrams. We then apply this result to the problem of finding the minimum Hausdorff distance between two point sets in the plane under Euclidean motion. We show that this distance can be computed in time 0((m + n)⁶log(mn)), where the two sets contain m and n points respectively."
Finding convex edge groupings in an image by Daniel P Huttenlocher( Book )

2 editions published in 1990 in English and held by 5 WorldCat member libraries worldwide

From this local neighborhood a local convexity graph is constructed. This planar graph encodes which neighboring image edges could be part of a convex group. A cycle in the graph corresponds to a group of image edges that form a convex region. The structure of the graph guarantees that each image edge belongs to at most one such cycle, thus limiting the total number of groups to O(n) for n image edges. We have implemented the method and found that it is efficient in practice as well as in theory
The upper envelope of Voronoi surfaces and its applications by Daniel P Huttenlocher( Book )

3 editions published in 1991 in English and held by 5 WorldCat member libraries worldwide

We derive bounds on the number of vertices on the upper envelope of a collection of Voronoi surfaces, and provide efficient algorithms to calculate these vertices. We then discuss applications of the methods to the aforementioned problems."
On the sensitivity of the Hough transform for object recognition by William Eric Leifur Grimson( Book )

4 editions published in 1988 in English and held by 5 WorldCat member libraries worldwide

A common method for finding an object's pose is the generalized Hough transform, which accumulates evidence for possible coordinate transformations in a parameter space and takes large clusters of similar transformations as evidence of a correct solution. We analyze this approach by deriving theoretical bounds on the set of transformations consistent with each data-model feature pairing, and by deriving bounds on the likelihood of false peaks in the parameter space, as a function of noise, occlusion, and tessellation effects. We argue that blithely applying such methods to complex recognition tasks is a risky proposition, as the probability of false positives can be very high
A multi-resolution technique for comparing images using the Hausdorff distance by Daniel P Huttenlocher( Book )

3 editions published in 1992 in English and held by 4 WorldCat member libraries worldwide

Abstract: "The Hausdorff distance measures the extent to which each point of a 'model' set lies near some point of an 'image' set and vice versa. In this paper we describe an efficient method of computing this distance, based on a multi-resolution tessellation of the space of possible transformations of the model set. We focus on the case in which the model is allowed to translate and scale with respect to the image. This four- dimensional transformation space (two translation and two scale dimensions) is searched rapidly, while guaranteeing that no match will be missed. We present some examples of identifying an object in a cluttered scene, including cases where the object is partially hidden from view."
Comparing point sets under projection by Daniel P Huttenlocher( Book )

3 editions published in 1992 in English and held by 4 WorldCat member libraries worldwide

The basic issue is that for nearly all groups G, -̃ is not an equivalence relation (does not have an underlying invariant function). Despite this fact, however, -̃ does contain considerable geometric information. Thus we provide an algorithm for deciding whether P-̃Q that runs in time O(n³), where n is the cardinality of the sets P and Q."
Tracking non-rigid objects in complex scenes by Daniel P Huttenlocher( Book )

3 editions published in 1992 in English and held by 4 WorldCat member libraries worldwide

There is no assumption, however, that the two-dimensional image motion in successive frames will be small. Thus the method can track objects that move arbitrarily far in the image from one frame to the next."
Exploiting sequential phonetic constraints in recognizing spoken words by Daniel P Huttenlocher( Book )

2 editions published in 1985 in English and held by 4 WorldCat member libraries worldwide

Machine recognition of spoken language requires developing more robust recognition algorithms. A recent study by Shipman and Zue suggest using partial descriptions of speech sounds to eliminate all but a handful of word candidates from a large lexicon. The current paper extends their work by investigating the power of partial phonetic descriptions for developing recognition algorithms. First, we demonstrate that sequences of manner of articulation classes are more reliable and provide more constraint than certain other classes. Alone these results are of limited utility, due to the high degree of variability in natural speech. This variability is not uniform however, as most modifications and deletions occur in unstressed syllables. Comparing the relative constraint provided by sounds in stressed versus unstressed syllables, we discover that the stressed syllables provide substantially more constraint. This indicates that recognition algorithms can be made more robust by exploiting the manner of articulation information in stressed syllables. Keywords: Natural constraints, Partial information, Word recognition, Speech recognition
Visually-guided navigation by comparing two-dimensional edge images by Daniel P Huttenlocher( Book )

2 editions published in 1994 in English and held by 4 WorldCat member libraries worldwide

Abstract: "We present a method for navigating a robot from an initial position to a specified landmark in its visual field, using a sequence of monocular images. The location of the landmark with respect to the robot is determined using the change in size and location of the landmark in the image, as a function of the motion of the robot. The landmark location is estimated after the first three images are taken, and this estimate is refined as the robot moves. The method can correct for errors in the robot motion, as well as navigate around obstacles. The obstacle avoidance is done using bump sensors, sonar and dead reckoning, rather than visual servoing. The method does not require prior calibration of the camera. We show some examples of the operation of the system."
Comparing images using the Hausdorff distance under translation by Daniel P Huttenlocher( Book )

2 editions published in 1991 in English and held by 4 WorldCat member libraries worldwide

In practice the methods are both highly efficient and simple to implement. The computation is in many ways similar to binary correlation, however it is more tolerant of perturbations in the locations of points because it measures proximity rather than exact superposition. We present a number of examples illustrating the operation of the approach, and compare it with correlation."
Detecting moving objects with a moving camera by comparing edge contours by Daniel P Huttenlocher( Book )

3 editions published in 1994 in English and held by 4 WorldCat member libraries worldwide

Abstract: "This paper introduces a method for detecting moving objects in a monocular image sequence that is obtained using a moving camera. The method first estimates the motion of the edge contours in a given image frame, by recovering a transformation that best matches each edge contour with the edges in the subsequent frame. Any contour that is not well accounted for by a single transformation is split into subparts. The transformation of each edge contour together with the relative spatial locations of the contours is used to partition the image into regions with similar motions. Hypotheses about the locations of possible moving objects are then made based on these motion regions. One of the key aspects of the approach is that it is based on estimating the motion of entire edge contours, as opposed to recovering a velocity field that measures the motion of individual points. We present some examples for image sequences taken of animate objects using a hand-held video camera."
On invariants of sets of points or line segments under projection by Daniel P Huttenlocher( Book )

3 editions published in 1992 in English and held by 4 WorldCat member libraries worldwide

Abstract: "We consider the problem of computing invariant functions of the image of a set of points or line segments in R³ under projection. Such functions are in principle useful for machine vision systems, because they allow different images of a given geometric object to be described by an invariant 'key'. We show that if a geometric object consists of an arbitrary set of points or line segments in R³, and the object can undergo a general rotation, then there are no invariants of its image under projection. For certain constrained rotations, however, there are invariants (e.g., rotation about the viewing direction). Thus we precisely delimit the conditions for the existence or nonexistence of invariants of arbitrary sets of points or line segments under projection."
Special issue on interpretation of 3-D scenes( Book )

in English and held by 3 WorldCat member libraries worldwide

Recognizing 3D objects from 2D images : an error analysis by William Eric Leifur Grimson( Book )

1 edition published in 1992 in English and held by 3 WorldCat member libraries worldwide

Abstract: "Many recent object recognition systems use a small number of pairings of data and model features to compute the 3D transformation from a model coordinate frame into the sensor coordinate system. In the case of perfect image data, these systems seem to work well. With uncertain image data, however, the performance of such methods is less well understood. In this paper, we examine the effects of two- dimensional sensor uncertainty on the computation of three-dimensional model transformations. We use this analysis to bound the uncertainty in the transformation parameters, as well as the uncertainty associated with applying the transformation to map other model features into the image. We also examine the effects of the transformation uncertainty on the effectiveness of recognition methods."
On the verification of hypothesized matches in model-based recognition by William Eric Leifur Grimson( Book )

3 editions published in 1989 in English and held by 3 WorldCat member libraries worldwide

In model-based recognition, ad hoc techniques are used to decide if a match of data to model is correct. Generally an empirically determined threshold is placed on the fraction of model features that must be matched. We rigorously derive conditions under which to accept a match, relating the probability of a random match to the fraction of model features accounted for, as a function of the number of model features, number of image features and the sensor noise. We analyze some existing recognition systems and show that our method yields results comparable with experimental data
An Efficiently computable metric for comparing polygonal shapes by E. M Arkin( Book )

3 editions published between 1989 and 1991 in English and held by 2 WorldCat member libraries worldwide

Model-based recognition is concerned with comparing a shape A, which is stored as a model for some particular object, with a shape B, which is found to exist in an image. If A and B are close to being the same shape, then a vision system should report a match and return a measure of how good that match is. To be useful this measure should satisfy a number of properties, including: (1) it should be a metric, (2) it should be invariant under translation, rotation, and change-of-scale, (3) it should be reasonably easy to compute, and (4) it should match our intuition (i.e., answers should be similar to those that a person might give). We develop a method for comparing polygons that has these properties. The method works for both convex and nonconvex polygons and runs in time O(mn log mn) where m is the number of vertices in one polygon and n is the number of vertices in the other. Some examples are presented that show the method produces answers that are intuitively reasonable
Recognizing rigid objects by aligning them with an image by Massachusetts Institute of Technology( Book )

3 editions published in 1987 in English and held by 2 WorldCat member libraries worldwide

This paper presents an approach to recognition where an object is first aligned with an image using a small number of pairs of model and image features, and then the aligned model is compared directly against the image. For instance, the position, orientation, and scale of an object in three-space can be determined from three pairs of corresponding model and image points. By using a small fixed number of features to determine position and orientation, the alignment method avoids structuring the recognition process as an exponential search. To demonstrate the method, we present some examples of recognizing flat rigid objects with arbitrary three-dimensional position, orientation, and scale, from a single two-dimensional image. The recognition system chooses features for alignment using a scale-space segmentation of edge contours. Segments are described in terms of both their shape and the structure of the scale-space hierarchy at the next finer level, producing distinctive features for use in finding possible alignments. Finally, the method is extended to the domain of non-flat objects as well
 
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Alternative Names
Daniel P. Huttenlocher American university teacher

Daniel P. Huttenlocher Amerikaans hoogleraar

Daniel P. Huttenlocher US-amerikanischer Informatiker

Languages
English (57)