UAV IMAGING G6: Shen, Yubing, Yushi. PANDABOARD Dual-Core 1.2 GHz ARM Cortex-A9 CPU 1 GB DDR2 SDRAM 5V Power Supply.

Slides:



Advertisements
Similar presentations
CCD Camera with USB2.0 & GIGABIT interfaces for the Pi of The Sky Project Grzegorz Kasprowicz PERG dr inż. Krzysztof Poźniak In cooperation with Soltan.
Advertisements

PHOTOGRAPHY DSLR – The Basics!. CONTROL OF LIGHT, MOTION AND BACKGROUND  1. Shutter Speed (Dial TV) SHUTTER SPEED Shutter Speed is controlled by the.
David Brenner, Caleb Douglas, Ahmed Elsherif, and Michael W. Timme Department of Electrical and Computer Engineering, UTSA TX David Brenner, Caleb.
Detection and Measurement of Pavement Cracking Bagas Prama Ananta.
By : Adham Suwan Mohammed Zaza Ahmed Mafarjeh. Achieving Security through Kinect using Skeleton Analysis (ASKSA)
Real-Time Accurate Stereo Matching using Modified Two-Pass Aggregation and Winner- Take-All Guided Dynamic Programming Xuefeng Chang, Zhong Zhou, Yingjie.
A Low-cost Attack on a Microsoft CAPTCHA Yan Qiang,
Team 4 Bryan Blancke Mark Heller Jeremy Martin Daniel Kim Facilitator: Dr. Aviyente Sponsor: ArcelorMittal Source: SMS.
Esmail Hadi Houssein ID/  „Motivation  „Problem Overview  „License plate segmentation  „Character segmentation  „Character Recognition.
Department of Electrical and Computer Engineering He Zhou Hui Zheng William Mai Xiang Guo Advisor: Professor Patrick Kelly ASLLENGE.
From Imagery to Map: Digital Photogrammetric Technologies 13 th International Scientific and Technical Conference From Imagery to Map: Digital Photogrammetric.
Drexel University Optical Imaging Research Group
Electrical and Computer Engineering SMART GOGGLES To Chong Ryan Offir Matt Ferrante James Kestyn Advisor: Dr. Tilman Wolf Preliminary Design Review.
Super Fast Camera System Performed by: Tokman Niv Levenbroun Guy Supervised by: Leonid Boudniak.
Super Fast Camera System Supervised by: Leonid Boudniak Performed by: Tokman Niv Levenbroun Guy.
You’ve Got SARS!! Group 6 Brent Anderson Lauren Cutsinger Martin Gilpatric Michael Oberg Matthew Taylor Capstone Spring 2006.
Neural Network-based Face Recognition, using ARENA Algorithm. Gregory Tambasis Supervisor: Dr T. Windeatt.
Tracking Migratory Birds Around Large Structures Presented by: Arik Brooks and Nicholas Patrick Advisors: Dr. Huggins, Dr. Schertz, and Dr. Stewart Senior.
Performed by: Niv Tokman Guy Levenbroun Instructor: Leonid Boudniak המעבדה למערכות ספרתיות מהירות High speed digital systems laboratory הטכניון - מכון.
California Car License Plate Recognition System ZhengHui Hu Advisor: Dr. Kang.
IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 20, NO. 11, NOVEMBER 2011 Qian Zhang, King Ngi Ngan Department of Electronic Engineering, the Chinese university.
Real-Time Face Detection and Tracking Using Multiple Cameras RIT Computer Engineering Senior Design Project John RuppertJustin HnatowJared Holsopple This.
Achieving True Color Fidelity
Digital Cameras (Basics) CCD (charge coupled device): image sensor Resolution: amount of detail the camera can capture Capturing Color: filters go on.
Conference Room Laser Pointer System Final Design Report Anna Goncharova Brent Hoover Alex Mendes.
COMM Subgroup Tomo Sugano (Primarily served as COMM personnel) Tasks –Started out by helping Relative Orbit team with differential delta-V requirement.
Conference Room Laser Pointer System Anna Goncharova, Brent Hoover, Alex MendesSponsored by Dr. Jeffrey Black Overview The project concept was developed.
USB & Analog Connection Windows, Mac, Linux Compatibility UVC (USB Video Class) Standard.
Digital Graphics and Computers. Hardware and Software Working with graphic images requires suitable hardware and software to produce the best results.
1 Daniel Micheletti Darren Allen Daniel Mazo Jon Lamb Lyle Johnson Pixel Perfect WiCam: A Wireless Digital Camera Presented by : Kyle Swenson.
Eye Detector Project Midterm Review John Robertson Roy Nguyen.
Virtual Modeling Simulation of a camera, placed on the robot Author Astapkovich Dmitry,
1 Warsaw University of Technology Faculty of Electronics and Information Technology Institute of Electronic Systems HARDWARE SIMULATOR of the high-resolution.
GeoVision INC GV-SDI-204.  GeoVision INC  Page 2 Contents  GV-SDI-204 ◆ is what ◆ Appearance ◆ let it work ◆ CPU usage competition ◆ Mix it with other.
PHOTOGRAPHY DSLR – The Basics!. CONTROL OF LIGHT, MOTION AND BACKGROUND  1. Shutter Speed (Dial TV) SHUTTER SPEED Shutter Speed is controlled by the.
Shutter Timing and Flash Synchronization System Joel Hoffa Shaun Pontsler November 10, 2005 Advisor: Professor Herr.
Energy efficient calculations of text similarity measure on FPGA-accelerated computing platforms Michał Karwatowski 1,2, Paweł Russek 1,2, Maciej Wielgosz.
FPGA-based Platform for Real-Time Stereo Vision Sergiy Zhelnakov, Pil Woo (Peter) Chun, Valeri Kirischian Supervisor: Dr. Lev Kirischian Reconfigurable.
Hardware. Make sure you have paper and pen to hand as you will need to take notes and write down answers and thoughts that you can refer to later on.
Tracking with CACTuS on Jetson Running a Bayesian multi object tracker on a low power, embedded system School of Information Technology & Mathematical.
Visual Tracking on an Autonomous Self-contained Humanoid Robot Mauro Rodrigues, Filipe Silva, Vítor Santos University of Aveiro CLAWAR 2008 Eleventh International.
© 2004 Xilinx, Inc. All Rights Reserved Implemented by : Alon Ben Shalom Yoni Landau Project supervised by: Mony Orbach High speed digital systems laboratory.
Hands-Free Camera Controller Jeffrey Gould. Overview Introduction –Background –Design Criteria Components Sensor Mapping Problems Demonstration Future.
Jason Li Jeremy Fowers 1. Speedups and Energy Reductions From Mapping DSP Applications on an Embedded Reconfigurable System Michalis D. Galanis, Gregory.
Detection Scheme of Single Shot Time Resolved X-ray Emission Spectroscopy of Chemical Dynamics at LCLS Kathleen R. Geyer August 12, 2010 Mentor: Dennis.
ESPL 1 Motivation Problem: Amateur photographers often take low- quality pictures with digital still camera Personal use Professionals who need to document.
Implementing Fast Image Processing Pipelines in a Codesign Environment Accelerate image processing tasks through efficient use of FPGAs. Combine already.
SUREILLANCE IN THE DEPARTMENT THROUGH IMAGE PROCESSING F.Y.P. PRESENTATION BY AHMAD IJAZ & UFUK INCE SUPERVISOR: ASSOC. PROF. ERHAN INCE.
Vision-Guided Robot Position Control SKYNET Tony BaumgartnerBrock Shepard Jeff Clements Norm Pond Nicholas Vidovich Advisors: Dr. Juliet Hurtig & Dr. J.D.
Learning Roomba Module 5 - Localization. Outline What is Localization? Why is Localization important? Why is Localization hard? Some Approaches Using.
Unsupervised Automation of Photographic Composition Rules Serene Banerjee and Brian L. Evans
Auto Focus System based on RTS2 and EPICS Jiajing Liu, Guangyu Zhang, Jian Wang Modern Physics Department, University of Science and.
BY Names of team mates and USN numbers TITLE OF YOUR PROJECT college logo example.
Robust Segmentation of Freight Containers in Train Monitoring Videos Qing-Jie Kong*, Avinash Kumar**, Narendra Ahuja**,Yuncai Liu* **Department of Electrical.
Motion tracking TEAM D, Project 11: Laura Gui - Timisoara Calin Garboni - Timisoara Peter Horvath - Szeged Peter Kovacs - Debrecen.
SMART CAMERAS AS EMBEDDED SYSTEM SMVEC. SMART CAMERA  See, think and act  Intelligent cameras  Embedding of image processing algorithms  Can be networked.
Automatic License Plate Recognition for Electronic Payment system Chiu Wing Cheung d.
Depth Analysis With Stereo Cameras
Hardware Implementation of CTIS Reconstruction Algorithms
Reconstruction For Rendering distribution Effect
Picture Analysis Answer the questions on each slide about that particular picture shown.
PRESENTED BY Yang Jiao Timo Ahonen, Matti Pietikainen
VUMC Soil Worm Activity Monitor
Yun-FuLiu Jing-MingGuo Che-HaoChang
Focusing on the big picture.
Fast Camera: Process Data on the Fly
Electronic Door Unlock with Face Recognition
Real-time Object Recognition using deep learning-Raspberry Pi
Jetson-Enabled Autonomous Vehicle ROS (Robot Operating System)
Jetson-Enabled Autonomous Vehicle
Presentation transcript:

UAV IMAGING G6: Shen, Yubing, Yushi

PANDABOARD Dual-Core 1.2 GHz ARM Cortex-A9 CPU 1 GB DDR2 SDRAM 5V Power Supply

CHAMELEON CAMERA USB 2.0 CCD Sensor Global Shutter 1296 x 964 Pixels

libdc1394 SOFTWARE ENVIRONMENT

SOFTWARE DIAGRAM

DETECTION ALGORITHM -EDGE DETECTION

RECOGNITION ALGORITHM -EDGE CONNECTION

SUITABLE FOR OUR TASK Strong tolerance to blurry pictures High performance

SPEED COMPARISON

TEST RESULT Detection Accuracy: 70% ~ 95% (depending the background complexity) Maximum Capturing Rate: 6.8 FPS Average Processing Rate: 5.0 FPS

DEMONSTRATION

CONCLUSION This project is an on-board image processing system Main Hardware Components: Pandaboard ES & Chameleon CMLN-13S2C USB Camera Software: Image capturing, image processing & image transmission

QUESTION?

THANK YOU