Richard F. Vaz

Linear signal decomposition approach to affine-invariant contour identification

A means for the identification of objects from contours despite affine transform induced distortions that takes the form of a linear signal space decomposition has been obtained. This new technique also yields robust estimates of the affine transformation from which the 3-D rotations of a near planar object may be obtained. The ability to determine object identity and orientation from a singe model representation without iteration or combinatorial search proceeds from the use of affine invariant differential measures that may be derived via Lie group theory. The resulting technique is extremely robust in the presence of noise (or nonplanarity of the object) owing to the error rejection properties of the signal space projection operations. The resulting algorithm is amenable to high-speed implementation with digital signal processing hardware architectures because it can be reduced to a sequence of linear 1-D signal processing operations. Included in this paper are a number of demonstration results that illustrate the resilience of the solutions in the presence of severe nonaffine distortion and pixelization error.

A linear signal decomposition approach to affine invariant contour identification

Means for the identification of objects from contours despite affine transform induced distortions using a linear signal space decomposition are described. This technique also yields robust estimates of the 3-D rotations of a near planar object. The ability to determine object identity and orientation from a single model representation without iteration or combinatorial search proceeds from the use of affine invariant differential measures derived via Lie group theory. The technique is extremely robust owing to the error rejection properties of signal space projections. Results illustrating the resilience of the solutions in the presence of severe non-affine distortion and pixelization are given.

Generation of affine invariant local contour feature data

Abstract A method for determining 3-D object orientation from a single 2-D image with incomplete data is discussed. Locally determined affine invariant data from planar object features allows efficient solution for transformation parameters using the generalized Hough transform.

Experiential learning with a global perspective: overseas senior design projects

All WPI undergraduate students complete three required projects, including a senior-level capstone design project that is equivalent in credit to three courses. Over 50% of WPI students complete at least one of their projects overseas at one of WPIs residential Project Centers located around the globe. Here, we describe two Project Centers-in Limerick, Ireland and Copenhagen, Denmark-at which teams of WPI students spend an academic term completing electrical and computer engineering design projects for industrial sponsors. Examples of student projects are given, as are details of the learning outcomes and accreditation evidence they provide. Finally, logistical and operational issues are discussed.

Efficient implementation of the analytic Hough transform for exact linear feature extraction

In this paper an implementation of the analytic Hough transform (AHT) for exact digital line detection is developed that employs a new, efficient data structure. This new structure eliminates the need to represent each digital line parameter region that is developed during the analysis of the image by empolying a region divider representation. A relative storage scheme is employed thast permits reconstruction of region occupancy information during the search for digital line support. Furthermore, it is shown that all values in the AHT data structure may be stored as rational numbers with fixed and finite numerator and denominator ranges defined by the image resolution. As a result, all floating point computations are replaced by faster, fixed word-size, integer operations.

A Novel Indoor Navigation Approach Employing Motion Statistics

In this paper, we devised a novel indoor navigation system based on a probabilistic approach that employs data from the wireless adapter, accelerometer, and compass of the mobile device in order to determine user position. A routing algorithm employed by the device calculates the optimal path between user position and its destination. Experimental results verified that two meter accuracy was achieved by the proposed design. This technique shows promise for future handheld indoor navigation systems that can be used in malls, museums, hospitals, and college campuses.

An energy spreading technique for cognitive radio networks

This paper presents a novel cognitive radio network architecture that optimizes information routing to preserve battery capacity while maintaining an acceptable signal quality. This is implemented via the monitoring of current link quality and battery levels of the nodes within the network and by performing a routing algorithm to optimize the signal quality of the links and the battery life of the nodes. A weight-based modification of Dijkstras algorithm and a rank-based routing algorithm that calculated and maximized the nodes battery lives were implemented. Experimental results show that the network performs the entire optimization process successfully 87.5% of 40 test trials.

ECE as a pre-professional undergraduate program

Rapid changes and broadening scope in electrical and computer engineering (ECE) combine with other pressures to make BS degree-level preparation for the future increasingly difficult. The proposed solution is a pre-professional degree, focusing on broad educational outcomes and featuring nontraditional learning experiences, leading to a variety of graduate school career tracks. It is argued that this approach is potentially a productive way in which to address declining interest in engineering by its traditional students, as well as marginal increases in interest by women and minorities. The pre-professional degree is the logical result of the forces on undergraduate ECE education, and it can address the challenges of preparing students for leadership and success, not just survival, in a future in which the only constant will be change. Representative educational objectives and program outcomes for such a pre-professional program are presented.

Quadratic assignment problems generated with the Palubetskis algorithm are degenerate

The quadratic assignment problem (QAP) is a combinatorial optimization problem that arises in many applications such as the allocation of processes in distributed computer systems. The QAP is NP-hard and therefore no algorithms are known for solving the QAP in polynomial time. For this reason a variety of heuristic methods have been proposed for this problem. In order to evaluate heuristics, Palubetskis proposed an algorithm that generates QAPs with known optimal solution value. We show in this paper that given a Palubetskis instance (but not its optimal value) the corresponding optimal value can be determined via a linear program, polynomial in the input data, i.e., in polynomial time. This implies that problems generated by the Palubetskis method belong to a simple and degenerate subclass of QAPs and are therefore not appropriate for algorithm testing. The proof technique suggests moreover a new lower bound for Euclidean QAPs. >

Long term impacts of off-campus project work on student learning and development

This paper presents findings from an evaluation study of engineering alumni who experienced a project-based undergraduate curriculum, examining differences in reported learning gains between alumni who completed projects on campus and those who completed projects in off-campus locations, both domestic and international. Survey respondents who had completed at least one project away from campus reported significantly greater positive impact not only in areas in which it was anticipated - expansion of world views and personal development and enrichment - but in very specific areas of professional development related to interpersonal relationships, communication skills, and understanding of ethical responsibilities.