An FPGA based high performance optical flow hardware design for computer vision applications

Date

2013-05-01

Author

Gultekin, Gokhan Koray
Saranlı, Afşar

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

187
views

0
downloads

Optical Flow (OF) information is used in higher level vision tasks in a variety of computer vision applications. However, its use in resource constrained applications such as small-scale mobile robotic platforms is limited because of the high computational complexity involved. The inability to compute the OF vector field in real-time is the main drawback which prevents these applications to efficiently utilize some successful techniques from the computer vision literature. In this work, we present the design and implementation of a high performance FPGA hardware with a small footprint and low power consumption that computes OF at a speed exceeding real-time performance. A well known OF algorithm by Horn and Schunck is selected for this baseline implementation. A detailed multiple-criteria performance analysis of the proposed hardware is presented with respect to computation speed, resource usage, power consumption and accuracy compared to a PC based floating-point implementation. The implemented hardware computes OF vector field on 256 x 256 pixels images in 3.89 ms i.e. 257 fps. Overall, the proposed implementation achieves a superior performance in terms of speed, power consumption and compactness while there is minimal loss of accuracy. We also make the FPGA design source available in full for research and academic use.

Subject Keywords

FPGA, Embedded Machine Vision, Optical Flow, Real Time Image Processing, Horn And Schunck Algorithm

URI

https://hdl.handle.net/11511/36337

Journal

MICROPROCESSORS AND MICROSYSTEMS

DOI

https://doi.org/10.1016/j.micpro.2013.01.001

Collections

Department of Electrical and Electronics Engineering, Article

Suggestions

OpenMETU
Core

An FPGA based high performance optical flow hardware design for autonomous mobile robotic platforms Gültekin, Gökhan Koray; Saranlı, Afşar; Department of Electrical and Electronics Engineering (2010) Optical flow is used in a number of computer vision applications. However, its use in mobile robotic applications is limited because of the high computational complexity involved and the limited availability of computational resources on such platforms. The lack of a hardware that is capable of computing optical flow vector field in real time is a factor that prevents the mobile robotics community to efficiently utilize some successful techniques presented in computer vision literature. In this thesis work,...
A Confidence Ranked Co-Occurrence Approach for Accurate Object Recognition in Highly Complex Scenes Angın, Pelin (2013-01-01) Real-time and accurate classification of objects in highly complex scenes is an important problem for the Computer Vision community due to its many application areas. While boosting methods with the sliding window approach provide fast processing and accurate results for particular object categories, they cannot achieve the desired performance for more involved categories of objects. Recent research in Computer Vision has shown that exploiting object context through relational dependencies between object ca...
A new approach to shutterless operation of microbolometer based infrared cameras Çavdar, Semih; Akın, Tayfun; Department of Electrical and Electronics Engineering (2021-2-03) This thesis presents an algorithm for the shutterless operation of microbolometer based infrared imaging systems. The active material of the microbolometer used in the thesis is vanadium oxide and it is produced in METU MEMS Center. The array size of the microbolometer is 480x640 and pixel pitch is 17 μm. The microbolometer has a CTIA type readout circuit which consists of detector and reference resistance. Voltage values are optimized at steady-state considering interactions between pixels in the focal pla...
Design and Optimization of Nanoantennas for Nano-Optical Applications Işıklar, Göktuğ; Ergül, Özgür Salih; Department of Electrical and Electronics Engineering (2020-9) In this study, design and simulation of plasmonic nanoantenna structures to obtain high power enhancement capabilities at optical frequencies, as well as utilization of nanoantennas for imaging and sensing applications are presented. Plasmonic characteristics of nanoantennas, which depend on many parameters, such as material, frequency, geometry, and size, are investigated in detail via computational analyses of various nanoantenna structures. Numerical solutions of electromagnetic problems are performe...
A Fusion-Based Framework for Wireless Multimedia Sensor Networks in Surveillance Applications Yazici, Adnan; Koyuncu, Murat; Sert, Seyyit Alper; Yilmaz, Turgay (2019-01-01) Multimedia sensors enable monitoring applications to obtain more accurate and detailed information. However, the development of efficient and lightweight solutions for managing data traffic over wireless multimedia sensor networks (WMSNs) has become vital because of the excessive volume of data produced by multimedia sensors. As part of this motivation, this paper proposes a fusion-based WMSN framework that reduces the amount of data to be transmitted over the network by intra-node processing. This framewor...

Citation Formats

G. K. Gultekin and A. Saranlı, “An FPGA based high performance optical flow hardware design for computer vision applications,” MICROPROCESSORS AND MICROSYSTEMS, pp. 270–286, 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/36337.