Discrete Event Dynamic Systems: An Overview

In this report we present an overview for the development of a theory for discrete event dynamic systems (DEDS). Dynamic systems are usually modeled by finite state automata with partially overservable events together with a mechanism for enabling and disabling a subset of state transitions. DEDS are attracting considerable interests, current applications are found in manufacturing systems, communications and air traffic systems, future applications will include robotics, computer vision and AI. We will discuss notions of modeling, stability issues, observability, feedback and invertibility. We will also discuss the perturbation analysis technique (PA) for analyzing and describing the behavior of DEDs

Effect of Super Resolution on High Dimensional Features for Unsupervised Face Recognition in the Wild

Majority of the face recognition algorithms use query faces captured from uncontrolled, in the wild, environment. Often caused by the cameras limited capabilities, it is common for these captured facial images to be blurred or low resolution. Super resolution algorithms are therefore crucial in improving the resolution of such images especially when the image size is small requiring enlargement. This paper aims to demonstrate the effect of one of the state-of-the-art algorithms in the field of image super resolution. To demonstrate the functionality of the algorithm, various before and after 3D face alignment cases are provided using the images from the Labeled Faces in the Wild (lfw). Resulting images are subject to testing on a closed set face recognition protocol using unsupervised algorithms with high dimension extracted features. The inclusion of super resolution algorithm resulted in significant improved recognition rate over recently reported results obtained from unsupervised algorithms

Computing a Complete Histogram of an Image in Log(n) Steps and Minimum Expected Memory Requirements Using Hypercubes

This work first reviews an already-developed, existing deterministic parallel algorithm to compute the complete histogram of an image in optimal number of steps (log n) on a hypercube architecture and utilizing memory space on the order of O(x1/2 log x), where x is the number of gray levels in the image, at each processing element. The paper then introduces our improvement to this algorithm’s memory requirements by introducing the concept of randomization into the algorithm

Performance Evaluation via Perturbation Analysis

In this paper we present an overview for the development of a theory for analyzing and predicting the behavior if discrete event dynamic systems (DEDS). DEDS are dynamic systems in which state transitions are caused by internal, discrete events in the system. DEDS are attracting considerable interest, current applications are found in manufacturing systems, communications and air traffic systems, future applications will include robotics, computer vision and artificial intelligence. We will discuss the perturbation analysis technique (PA) for evaluation the performance of DEDS

Model for Shape and Motion Perception

Copyright 1992 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.In this paper we describe an efficient system for recovering the 3-D motion and structure of visual systems from an evolving image sequence. The technique utilizes the image flow velocities in order to recover the 3-D parameters. We develop a real-time algorithm for recovering the 2-D flow vectors on the image plane with sub-pixel accuracy. The flow estimates are then examined for the possibilities for errors, mistakes and uncertainties in the visual system. Uncertainty models are developed for the sensor and for the image processing techniques being used. Further filtering and a rejection mechanism are then developed to discard unrealistic flow estimates. The 2-D flow models are then converted into 3-D uncertainty models for motion and structure. We further develop an algorithm which iteratively improves the 3-D solution given two successive image frames and then discuss a multi-frame algorithm that improves the solution progressively by using a large number of image frames.http://dx.doi.org/10.1117/12.13518

Modeling and recovering uncertainties in sense data

technical reportThis work examines closely the possibilities for errors, mistakes and uncertainties in sensing systems. We identify and suggest techniques for modeling, analyzing, and recovering these uncertainties. This work concentrates on uncertainties in visual sensing to recover 3-D structure and motion characteristics of the scene under observation, however, we conjecture that the approaches described here are suitable for other sensors and parameters to be recovered. The computed uncertainties are utilized for reconstructing the scene under observation

Compressed Transmission Mode: An Optimizing Decision Tool

In this paper we address the problem of host to host communication. In particular, we discuss the issue of efficient and adaptive transmission mechanisms over possible physical links. We develop a tool for making decisions regarding the flow of control sequences and data from and to a host. The issue of compression is discussed in details, a decision box and an optimizing tool for finding the appropriate thresholds for a decision are developed. Physical parameters like the data rate, bandwidth of the communication medium, distance between the hosts, band rate, levels of discretization, signal to noise ratio and propagation speed of the signal are taken into consideration while developing our decision system. Theoretical analysis is performed to develop mathematical models for the optimization algorithm. Simulation models are also developed for testing both the optimization and the decision tool box

Operator/System Communication : An Optimizing Decision Tool

Copyright 1990 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.In this paper we address the problem of operator/system communication. In particular, we discuss the issue of efficient and adaptive transmission mechanisms over possible physical links. We develop a tool for making decisions regarding the flow of control sequences and data from and to the operator. The issue of compression is discussed in details, a decision box and an optimizing tool for finding the appropriate thresholds for a decision are developed. Physical parameters like the data rate, bandwidth of the communication medium, distance between the operator and the system, baud rate, levels of discretization, signal to noise ratio and propagation speed of the signal are taken into consideration while developing our decision system. Theoretical analysis is performed to develop mathematical models for the optimization algorithm. Simulation models are also developed for testing both the optimization and the decision tool box.http://dx.doi.org/10.1117/12.2549

Observing a Moving Agent

We address the problem of observing a moving agent. In particular, we propose a system for observing a manipulation process, where a robot hand manipulates an object. A discrete event dynamic system (DEDS) from work is developed for the hand/object interaction over time and a stabilizing observer is constructed. Low-level modules are developed for recognizing the events that causes state transitions within the dynamic manipulation system. The work examines closely the possibilities for errors, mistakes and uncertainties in the manipulation system, observer construction process and event identification mechanisms. The system utilizes different tracking techniques in order to observe the task in an active, adaptive and goal-directed manner

An Adaptive and Efficient System for Computing the 3-D Reachable Workspace

In this paper, we present an efficient system for computing the 3-D reachable workspace for redundant manipulators with joint limits. In our system, we have decomposed the 3-D reachable workspace problem into two major sub-problems: workspace point generation and surface computation. We describe different algorithms that are used to build these modules. Finally, we discuss the advantages offered by our system