List processing primitives for BASIC

This paper describes list-processing primitives which form a component of an interactive graphics system. This system, developed at Bowling Green State University, has a plasma display panel as its central component.This system comprises a BASIC interpreter to which has been added a rich variety of graphic and list-processing primitives. These are implemented as additional BASIC verbs.The list-processing primitives permit creation of arbitrarily complex list structures: trees, multiply linked lists, etc. can all be constructed. It is possible to manipulate list and node names in a natural way. Lists, sublists, and nodes can be added and deleted, lists can be searched, and the list space dynamically reformatted if desired.The system also includes an extremely flexible mechanism for describing and manipulating data contained in a node. Several data types are available ranging from floating point to variable-length integer. It is possible to manipulate data at the bit level.This facility greatly increases the flexibility of the graphic system since it is possible to represent structural relationships between the components of a figure.     

Extraction of Film Takes for Cinematic Analysis

In this paper, we focus on the ‘reverse editing’ problem in movie analysis, i.e., the extraction of film takes, original camera shots that a film editor extracts and arranges to produce a finished scene. The ability to disassemble final scenes and shots into takes is essential for nonlinear browsing, content annotation and the extraction of higher order cinematic constructs from film. A two-part framework for take extraction is proposed. The first part focuses on the filtering out action-driven scenes for which take extraction is not useful. The second part focuses on extracting film takes using agglomerative hierarchical clustering methods along with different similarity metrics and group distances and demonstrates our findings with 10 movies.     

MIL primitives for querying a fragmented world

In query-intensive database application areas, like decision support and data mining, systems that use vertical fragmentation have a significant performance advantage. In order to support relational or object oriented applications on top of such a fragmented data model, a flexible yet powerful intermediate language is needed. This problem has been successfully tackled in Monet, a modern extensible database kernel developed by our group. We focus on the design choices made in the Monet interpreter language (MIL), its algebraic query language, and outline how its concept of tactical optimization enhances and simplifies the optimization of complex queries. Finally, we summarize the experience gained in Monet by creating a highly efficient implementation of MIL. Received November 10, 1998 / Accepted March 22, 1999     

New application methods for word-oriented cryptographic primitives

Modern software oriented symmetric ciphers have become a key feature in utilizing word-oriented cryptographic primitives.Using the output sequence,in the order of its generation,of a word-oriented cryptographic primitive in the same way as traditional bit-oriented primitives,we can expose the intrinsic weakness of these primitives,especially for word-oriented linear feedback shift registers,T-functions,and so on.Two new methods for using word-oriented cryptographic primitives are presented in this paper,that is,the extracted state method and cascading extracted coordinate method.Using a T-function as an example,we research the different cryptographic properties of the output sequences of the original method and the two proposed methods,focusing mainly on period,linear complexity,and k-error linear complexity.Our conclusions show that the proposed methods could enhance at low cost the cryptographic properties of the output sequence.As a result,since the new methods are simple and easy to implement,they could be used to design new word-oriented cryptographic primitives.     

Policy search for motor primitives in robotics

Many motor skills in humanoid robotics can be learned using parametrized motor primitives. While successful applications to date have been achieved with imitation learning, most of the interesting motor learning problems are high-dimensional reinforcement learning problems. These problems are often beyond the reach of current reinforcement learning methods. In this paper, we study parametrized policy search methods and apply these to benchmark problems of motor primitive learning in robotics. We show that many well-known parametrized policy search methods can be derived from a general, common framework. This framework yields both policy gradient methods and expectation-maximization (EM) inspired algorithms. We introduce a novel EM-inspired algorithm for policy learning that is particularly well-suited for dynamical system motor primitives. We compare this algorithm, both in simulation and on a real robot, to several well-known parametrized policy search methods such as episodic REINFORCE, ??Vanilla?? Policy Gradients with optimal baselines, episodic Natural Actor Critic, and episodic Reward-Weighted Regression. We show that the proposed method out-performs them on an empirical benchmark of learning dynamical system motor primitives both in simulation and on a real robot. We apply it in the context of motor learning and show that it can learn a complex Ball-in-a-Cup task on a real Barrett WAM? robot arm.     

Warp-based helical implicit primitives

Implicit modeling with skeleton-based primitives has been limited up to now to planar skeleton elements, since no closed-form solution was found for convolution along more complex curves. We show that warping techniques can be adapted to efficiently generate convolution-like implicit primitives of varying radius along helices, a useful 3D skeleton found in a number of natural shapes. Depending on a single parameter of the helix, we warp it onto an arc of circle or onto a line segment. For those latter skeletons closed-form convolutions are known for entire families of kernels. The new warps introduced preserve the circular shape of the normal cross section to the primitive.     

Some extended semaphore primitives

Summary This paper presents a proposal for synchronizing primitives obtained as an extension of Dijkstra's P, V primitives. The extended primitives are shown to be complete: they can represent any desired interaction between processes without the use of conditionals. The usefulness of these primitives is illustrated by presenting simple solutions to a series of coordination problems of increasing complexity. Two selected problems are used to illustrate disadvantages of existing synchronizing mechanisms. The extended primitives shift some of the burden from the programmer to the system since they are easier to use but more difficult to implement. However, even though each primitive operation may take longer to execute (as compared to the simple P, V primitives) the total system overhead can be substantially less especially for complex coordination problems. The paper presents a straightforward but efficient implementation of the extended primitives.This work was supported in part by the U.S. Atomic Energy Commision under contract AT(11-1 3288) and in part by the Joint Services Electronics Program under contract AFOSR F4620-76-C-0089     

Cords: geometric curve primitives for modeling contact

Curves are perhaps the most versatile of modeling primitives in computer graphics. They define a rough structure for many surface-generation algorithms and are often fit to meaningful surface features for further shape modeling. Deformable objects such as hair and fur are simulated on finite element curve discretizations. Motion paths for planning and animation applications are tied to underlying curves. In this article we present a geometric curve primitive, known as a cord, which allows for interactive modeling of curves that contact complex geometry.     

Human-inspired force compliant grasping primitives

We address the problem of grasping everyday objects that are small relative to an anthropomorphic hand, such as pens, screwdrivers, cellphones, and hammers from their natural poses on a support surface, e.g., a table top. In such conditions, state of the art grasp generation techniques fail to provide robust, achievable solutions due to either ignoring or trying to avoid contact with the support surface. In contrast, when people grasp small objects, they often make use of substantial contact with the support surface. In this paper we give results of human subjects grasping studies which show the extent and characteristics of environment contact under different task conditions. We develop a simple closed-loop hybrid grasping controller that mimics this interactive, contact-rich strategy by a position-force, pre-grasp and landing strategy for finger placement. The approach uses a compliant control of the hand during the grasp and release of objects in order to preserve safety. We conducted extensive robotic grasping experiments on a variety of small objects with similar shape and size. The results demonstrate that our approach is robust to localization uncertainties and applies to many everyday objects.     

Analogue VLSI primitives for perceptual tasks in machine vision

A variety of computational tasks in early vision can be formulated through lattice networks. The cooperative action of these networks depends upon the topology of interconnections, both feedforward and recurrent ones. The Gabor-like impulse response of a 2nd-order lattice network (i.e. with nearest and next-to-nearest interconnections) is analysed in detail, pointing out how a near-optimal filtering behaviour in space and frequency domains can be achieved through excitatory/inhibitory interactions without impairing the stability of the system. These architectures can be mapped, very efficiently at transistor level, on VLSI structures operating as analogue perceptual engines. The hardware implementation of early vision tasks can, indeed, be tackled by combining these perceptual agents through suitable weighted sums. Various implementation strategies have been pursued with reference to: (i) the algorithm-circuit mapping (current-mode and transconductor approaches); (ii) the degree of programmability (fixed, selectable and tunable); and (iii) the implementation technology (2 and 0.8 gate lengths). Applications of the perceptual engine to machine vision algorithms are discussed.     

A trained spin-glass model for grouping of image primitives

A method is presented that uses grouping to improve local classification of image primitives. The grouping process is based upon a spin-glass system, where the image primitives are treated as possessing a spin. The system is subject to an energy functional consisting of a local and a bilocal part, allowing interaction between the image primitives. Instead of defining the state of lowest energy as the grouping result, the mean state of the system is taken. In this way, instabilities caused by multiple minima in the energy are being avoided. The means of the spins are taken as the a posteriori probabilities for the grouping result. In the paper, it is shown how the energy functional can be learned from example data. The energy functional is defined in such a way that, in case of no interactions between the elements, the means of the spins equal the a priori local probabilities. The grouping process enables the fusion of the a priori local and bilocal probabilities into the a posteriori probabilities. The method is illustrated both on grouping of line elements in synthetic images and on vessel detection in retinal fundus images.     

Combining local belief from low-level primitives for perceptual grouping

Segmentation is usually unable to cope with artifacts due to slight change in lighting conditions or object occlusion for instance. That is why perceptual grouping is often used to overcome segmentation's lacks. This refers to the ability of human visual system to impose structure and regularity over signal-based data. Gestalt psychologists have exhibited some properties which are used during perceptual grouping, such as proximity, continuity, or symmetry. Then, some implementations of these have been proposed in computer vision. However, most of these works rely on contour-based primitives. Besides, they often use one single property to merge close regions, which may not be sufficiently robust. We propose a new framework for bottom-up perceptual grouping, which relies on a region-based segmentation. It allows us to use region or contour information, when it is the most suitable. Besides, we propose to trigger a grouping when several Gestalt properties support it. This could increase the robustness of perceptual grouping. We use Dempster–Shafer theory to combine the influence of several Gestalt properties over each grouping, as it is especially designed for this. We also present numerous promising results, which show the efficiency of our approach.     

Dispatcher primitives for the construction of operating system kernels

Summary The main subject of this paper is the definition of a general set of dispatcher primitives which have been proved to be a suitable basis for the structured design of operating system kernels. The use of the primitives in the construction of kernel programs is demonstrated.     

Efficient communication primitives on hypercubes

We give practical algorithms, complexity analysis and implementation for one-to-all broadcasting, all-to-all personalized communication and matrix transpose (with two-dimensional partitioning of the matrix) on hypercubes. We assume the following communication characteristics: circuit-switched, e-cube routing and one-port communication model. For one-to-all broadcasting, we give an algorithm that combines the well-known recursive doubling algorithm[1] and the algorithm based on edgedisjoint spanning trees[2]. The measured times of the combined algorithm are always superior to those of the edge-disjoint spanning tree algorithm and outperform the recursive doubling algorithm. For all-to-all personalized communication we propose a hybrid algorithm that combines the well-known recursive doubling algorithm[3,4] and the recently proposed direct-route algorithm[5,6] Our hybrid algorithm balances between data transfer time and start-up time of these two algorithms, and its communication complexity is estimated to be better than the two previous algorithms for a range of machine parameters. For matrix transpose with two-dimensional partitioning of the matrix, we relate a two-phase algorithm to the previous result in Reference 7. The algorithm is predicted to be better than the recursive transpose algorithm[8] by n nearest-neighbor communications[4]. It takes advantage of circuit-switched routing and is congestion-free within each phase. We also suggest a way of storing the matrix such that the transpose operation can be realized in one phase without congestion.