The curvature primal sketch

In this paper we introduce a novel representation of the significant changes in curvature along the bounding contour of planar shape. We call the representation the Curvature Primal Sketch because of the close analogy to the primal sketch representation advocated by Marr for describing significant intensity changes. We define a set of primitive parameterized curvature discontinuities, and derive expressions for their convolutions with the first and second derivatives of a Gaussian. We describe an implemented algorithm that computes the Curvature Primal Sketch by matching the multiscale convolutions of a shape, and illustrate its performance on a set of tool shapes. Several applications of the representation are sketched.     

Shape estimation from topographic primal sketch

In this paper, a technique for estimating object shape from topographic primal sketch is investigated. Given a gray tone image of a three-dimensional object, a topographic labeling of the image indicates the peaks and pits, ridges and valleys, and flats and hillsides of the underlying, continuous, gray tone surface. The patterns of these topographic labels capture information about the original three-dimensional object in the scene and about the illumination. In order to determine if estimation of three-dimensional shape from a topographic labeling is feasible, we have both analytically and experimentally determined the topographic labelings for images of some mathematically generated surfaces with varied directions of illumination. Our results indicate that such patterns do exist and will be useful in determining three-dimensional shape from two-dimensional images. A scheme for partial classification of three-dimensional object surface is proposed. Preliminary results are illustrated.     

The background primal sketch: An approach for tracking moving objects

In this paper we present an algorithm that integrates spatial and temporal information for the tracking of moving nonrigid objects. In addition, we obtain outlines of the moving objects.Three basic ingredients are employed in the proposed algorithm, namely, the background primal sketch, the threshold, and outlier maps. The background primal sketch is an edge map of the background without moving objects. If the background primal sketch is known, then edges of moving objects can be determined by comparing the edge map of the input image with the background primal sketch. A moving edge point is modeled as an outlier, that is, a pixel with an edge value differing from the background edge value in the background primal sketch by an amount larger than the threshold in the threshold map at the same physical location. The map that contains all the outliers is called the outlier map. In this paper we present techniques based on robust statistics for determining the background primal sketch, the threshold, and outlier maps.In an ideal situation the outlier map would contain the complete outlines of the moving objects. In practice, the outliers do not form closed contours. The final step of the algorithm employs an edge-guided morphological approach to generate closed outlines of the moving objects. The proposed approach has been tested on sequences of moving human blood cells (neutrophil) as well as of human body motion with encouraging results.     

Analysis of aerosol images using the scale-space primal sketch

We outline a method to analyze aerosol images using the scale-space representation. The pictures, which are photographs of an aerosol generated by a fuel injector, contain phenomena that by a human observer are perceived as periodic or oscillatory structures. The presence of these structures is not immediately apparent since the periodicity manifests itself at a coarse level of scale while the dominating objects in the images are small dark blobs, that is, fine scale objects. Experimentally, we illustrate that the scale-space theory provides an objective method to bring out these events. However, in this form the method still relies on a subjective observer in order to extract and verify the existence of the periodic phenomena.Then we extend the analysis by adding a recently developed image analysis concept called the scale-space primal sketch. With this tool, we are able to extract significant structures from a grey-level image automatically without any strong a priori assumptions about either the shape or the scale (size) of the primitives. Experiments demonstrate that the periodic drop clusters we perceived in the image are detected by the algorithm as significant image structures. These results provide objective evidence verifying the existence of oscillatory phenomena.     

An incremental primal sieve

Summary A new algorithm is presented for finding all primes between 2 and an incrementally increasing value n. The algorithm executes in linear arithmetic time and space. An outline is given to show how previously developed techniques can be applied to improve the efficiency of the algorithm to O(n/loglogn) time and space.     

An outline of the programming language SIMULA

Simulation is an important technique for solving problems in a variety of fields. Special languages have developed to serve as vehicles for system simulation as conventional languages seem to be quite inadequate to face this task.SIMULA is a powerful general purpose programming language which includes sophisticated simulation facilities. However, unfamiliarity with the language concepts and the restrictive amount of literature covering the language structure have led to the development of an inertia which has prevented many skilful programmers from using it. This paper presents an attempt towards introducing the concepts of simplicity and expressive power inherent in SIMULA to a wider audience.     

Left-Associative Grammar: An informal outline

The surface structures of natural language are linear. When we utter or understand a sentence, we process it word by word, starting at the beginning. But the associated semantic structures are hierarchical, expressed in terms of trees or set-theoretic relations. The correlation between linear syntax and hierarchical semantics is investigated in Left-Associative Grammar and the associated NEWCAT parsing algorithm. This paper gives a general outline of the linguistic theory. The formal algebraic and automata theoretic definitions will be presented in a second paper (Hausser, forthcoming), to appear in next issue of CaT.     

Computer recognition of the human spinal outline using radiographic image processing

This paper deals with the determination of the outline of the spinal column on a P-A X-ray projection using methods of computerized image processing. The work is part of a larger project the goal of which is to model and quantify the three dimensional geometrical characteristics of normal and pathological spinal columns as well as to theoretically analyze the mechanics of the diseased spine. The data obtained by computer processing of both the P-A and lateral views would serve as input to the model. In order to delineate the edges of the spine, a technique of guided edge detection is incorporated into a successive approximation method. The plan for the guided edge detection is initially obtained using vertical signatures, while subsequent plans are found by fitting polynomials to the detected edges. Results are presented to demonstrate the ability of the algorithm to determine the desired spinal outlines.     

An outline of a trust model for electronic commerce

A generic model of trust for electronic commerce is presented. The basic components of the model are party trust and control trust. It is argued that an agent's trust in a transaction with another party is a combination of the trust in the other party and the trust in the control mechanisms for the successful performance of the transaction. The generic trust model can be used for the design of trust related value-added services in electronic commerce. To illustrate this design use of the model, two activities in electronic commerce are compared that require trust, namely electronic payment and cross-border electronic trade. It is shown with the model that these two activities actually require two different types of trust, and that complete different services are needed to create these different types of trust.     

Training a support vector machine in the primal

Most literature on support vector machines (SVMs) concentrates on the dual optimization problem. In this letter, we point out that the primal problem can also be solved efficiently for both linear and nonlinear SVMs and that there is no reason for ignoring this possibility. On the contrary, from the primal point of view, new families of algorithms for large-scale SVM training can be investigated.     

A generative sketch model for human hair analysis and synthesis

In this paper, we present a generative sketch model for human hair analysis and synthesis. We treat hair images as 2D piecewise smooth vector (flow) fields and, thus, our representation is view-based in contrast to the physically-based 3D hair models in graphics. The generative model has three levels. The bottom level is the high-frequency band of the hair image. The middle level is a piecewise smooth vector field for the hair orientation, gradient strength, and growth directions. The top level is an attribute sketch graph for representing the discontinuities in the vector field. A sketch graph typically has a number of sketch curves which are divided into 11 types of directed primitives. Each primitive is a small window (say 5 /spl times/ 7 pixels) where the orientations and growth directions are defined in parametric forms, for example, hair boundaries, occluding lines between hair strands, dividing lines on top of the hair, etc. In addition to the three level representation, we model the shading effects, i.e., the low-frequency band of the hair image, by a linear superposition of some Gaussian image bases and we encode the hair color by a color map. The inference algorithm is divided into two stages: 1) We compute the undirected orientation field and sketch graph from an input image and 2) we compute the hair growth direction for the sketch curves and the orientation field using a Swendsen-Wang cut algorithm. Both steps maximize a joint Bayesian posterior probability. The generative model provides a straightforward way for synthesizing realistic hair images and stylistic drawings (rendering) from a sketch graph and a few Gaussian bases. The latter can be either inferred from a real hair image or input (edited) manually using a simple sketching interface. We test our algorithm on a large data set of hair images with diverse hair styles. Analysis, synthesis, and rendering results are reported in the experiments.     

How to solve linear differential equations: An outline

There are several definitions of closed form solutions to linear differential equations. In this paper, we look for the so-called Liouvillian solutions. Through examples, we give an overview of how the differential Galois theory leads to algorithms to find the Liouvillian solutions. We will outline the general ideas and results, but will give examples instead of proofs. This article was submitted by the author in English.     

First Sight: A human body outline labeling system

First Sight, a vision system in labeling the outline of a moving human body, is proposed in this paper. The emphasis of First Sight is on the analysis of motion information gathered solely from the outline of a moving human object. Two main processes are implemented in First Sight. The first process uses a novel technique to extract the outline of a moving human body from an image sequence. The second process, which employs a new human body model, interprets the outline and produces a labeled two-dimensional human body stick figure for each frame of the image sequence. Extensive knowledge of the structure, shape, and posture of the human body is used in the model. The experimental results of applying the technique on unedited image sequences with self-occlusions and missing boundary lines are encouraging     

Forging a discipline: An outline history of software engineering education

Software engineering education has a 30-year history. It is a story of academics struggling to fulfill industry needs with almost no support from computer science curriculum designers. It is a story of industry finally winning over some of academia to teach software engineering rather than vanilla computer science. It is a story of a discipline still incomplete, but having made great strides in the last decade. This paper discusses the succeeding eras of software engineering education, from lone teachers to master's curricula to undergraduate degree programs. Even though the maturity of the discipline is as yet unattained, it will achieve adult status through practice, not by waiting for academia to glacially catch up.