An Efficient and Cost Effective FPGA Based Implementation of the Viola-Jones Face Detection Algorithm

We present an field programmable gate arrays (FPGA) based implementation of the popular Viola-Jones face detection algorithm, which is an essential building block in many applications such as video surveillance and tracking. Our implementation is a complete system level hardware design described in a hardware description language and validated on the affordable DE2-115 evaluation board. Our primary objective is to study the achievable performance with a low-end FPGA chip based implementation. In addition, we release to the public domain the entire project. We hope that this will enable other researchers to easily replicate and compare their results to ours and that it will encourage and facilitate further research and educational ideas in the areas of image processing, computer vision, and advanced digital design and FPGA prototyping

Disaster Monitoring with Wikipedia and Online Social Networking Sites: Structured Data and Linked Data Fragments to the Rescue?

In this paper, we present the first results of our ongoing early-stage research on a realtime disaster detection and monitoring tool. Based on Wikipedia, it is language-agnostic and leverages user-generated multimedia content shared on online social networking sites to help disaster responders prioritize their efforts. We make the tool and its source code publicly available as we make progress on it. Furthermore, we strive to publish detected disasters and accompanying multimedia content following the Linked Data principles to facilitate its wide consumption, redistribution, and evaluation of its usefulness.Comment: Accepted for publication at the AAAI Spring Symposium 2015: Structured Data for Humanitarian Technologies: Perfect fit or Overkill? #SD4HumTech1

A Study of Speed of the Boundary Element Method as applied to the Realtime Computational Simulation of Biological Organs

In this work, possibility of simulating biological organs in realtime using the Boundary Element Method (BEM) is investigated. Biological organs are assumed to follow linear elastostatic material behavior, and constant boundary element is the element type used. First, a Graphics Processing Unit (GPU) is used to speed up the BEM computations to achieve the realtime performance. Next, instead of the GPU, a computer cluster is used. Results indicate that BEM is fast enough to provide for realtime graphics if biological organs are assumed to follow linear elastostatic material behavior. Although the present work does not conduct any simulation using nonlinear material models, results from using the linear elastostatic material model imply that it would be difficult to obtain realtime performance if highly nonlinear material models that properly characterize biological organs are used. Although the use of BEM for the simulation of biological organs is not new, the results presented in the present study are not found elsewhere in the literature.Comment: preprint, draft, 2 tables, 47 references, 7 files, Codes that can solve three dimensional linear elastostatic problems using constant boundary elements (of triangular shape) while ignoring body forces are provided as supplementary files; codes are distributed under the MIT License in three versions: i) MATLAB version ii) Fortran 90 version (sequential code) iii) Fortran 90 version (parallel code