Hardware Accelarated Visual Tracking Algorithms. A Systematic Literature Review

Many industrial applications need object recognition and tracking capabilities. The algorithms developed for those purposes are computationally expensive. Yet ,real time performance, high accuracy and small power consumption are essential measures of the system. When all these requirements are combined, hardware acceleration of these algorithms becomes a feasible solution. The purpose of this study is to analyze the current state of these hardware acceleration solutions, which algorithms have been implemented in hardware and what modifications have been done in order to adapt these algorithms to hardware.Siirretty Doriast

A real-time computer vision library for heterogeneous processing environments

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 69-70).With a variety of processing technologies available today, using a combination of different technologies often provides the best performance for a particular task. However, unifying multiple processors with different instruction sets can be a very ad hoc and difficult process. The Open Component Portability Infrastructure (OpenCPI) provides a platform that simplifies programming heterogeneous processing applications requiring a mix of processing technologies. These include central processing units (CPU), graphics processing units (GPU), field-programmable gate arrays (FPGA), general-purpose processors (GPP), digital signal processors (DSP), and high-speed switch fabrics. This thesis presents the design and implementation of a computer vision library in the OpenCPI framework, largely based on Open Source Computer Vision (OpenCV), a widely used library of optimized software components for real-time computer vision. The OpenCPI-OpenCV library consists of a collection of resource-constrained C language (RCC) workers, along with applications demonstrating how these workers can be combined to achieve the same functionality as various OpenCV library functions. Compared with applications relying solely on OpenCV, analogous OpenCPI applications can be constructed from many workers, often resulting in greater parallelization if run on multi-core platforms. Future OpenCPI computer vision applications will be able to utilize these existing RCC workers, and a subset of these workers can potentially be replaced with alternative implementations, e.g. on GPUs or FPGAs.by Tony J. Liu.M.Eng

Variational optic flow on the Sony PlayStation 3 – accurate dense flow fields for real-time applications

While modern variational methods for optic flow computation offer dense flow fields and highly accurate results, their computational complexity has prevented their use in many real-time applications. With cheap modern parallel hardware such as the Sony PlayStation 3 new possibilities arise. For a linear and a nonlinear variant of the popular combined local-global (CLG) method, we present specific algorithms that are tailored towards real-time performance. They are based on bidirectional full multigrid methods with a full approximation scheme (FAS) in the nonlinear setting. Their parallelisation on the Cell hardware uses a temporal instead of a spatial decomposition, and processes operations in a vector-based manner. Memory latencies are reduced by a locality-preserving cache management and optimised access patterns. With images of size 316×252 pixels, we obtain dense flow fields for up to 210 frames per second