DETECTION OF SURVIVORS USING THERMO & NIGHT VISION SYSTEM (UNDER DEVELOPMENT) Zbigniew Burciu, Teresa Abramowicz-Gerigk, Piotr Michna, Leszek Smolarek,

Slides:



Advertisements
Similar presentations
Miroslav Hlaváč Martin Kozák Fish position determination in 3D space by stereo vision.
Advertisements

Genoa, Italy September 2-4, th IEEE International Conference on Advanced Video and Signal Based Surveillance Combination of Roadside and In-Vehicle.
Laser Speckle Extensometer ME 53
Foundations of Medical Ultrasonic Imaging
NIGHT VISION GOGGLE DRIVING OPERATIONS Night Operations Depth Perception Height and Distance Visual Acuity Terrain Features & Obstacles Night Vision Techniques.
Cinematography The manipulations of the film strip by the camera in the shooting phase and by the laboratory in the developing phase. –Photographic aspects.
Joplin,Missouri Tornado Amanda Papp Pd.7. What is a Tornado And how do they form? A violently rotating column of air, pendant from a cumulonimbus cloud,
CASTLEFORD CAMERA CLUB DEPTH OF FIELD. DEPTH OF FIELD (DOF) DOF is the portion of a scene that appears acceptably sharp in the image.
Pore Detection in Small Diameter Bores The University of Michigan, Ann Arbor NSF Engineering Research Center for Reconfigurable Manufacturing Systems.
SEARCH PLAN VARIABLES CG Addendum Section H.5.
Vehicle-Infrastructure-Driver Interactions Research Unit
Recognition of Traffic Lights in Live Video Streams on Mobile Devices
Mobility Improves Coverage of Sensor Networks Benyuan Liu*, Peter Brass, Olivier Dousse, Philippe Nain, Don Towsley * Department of Computer Science University.
Camera Basics Level 1 Film Technology Canon XL-1.
FYPs supervised by KH Wong1 Final Year projects FYPs Supervised by KH Wong CSE CUHK.
Tracking a moving object with real-time obstacle avoidance Chung-Hao Chen, Chang Cheng, David Page, Andreas Koschan and Mongi Abidi Imaging, Robotics and.
CCU VISION LABORATORY Object Speed Measurements Using Motion Blurred Images 林惠勇 中正大學電機系
Computer Vision. Computer vision is concerned with the theory and technology for building artificial Computer vision is concerned with the theory and.
SNAKE ROBOTS TO THE RESCUE!. Introduction   Intelligent robots in SAR dealing with tasks in complex disaster environments   Autonomy, high mobility,
I mage and M edia U nderstanding L aboratory for Performance Evaluation of Vision-based Real-time Motion Capture Naoto Date, Hiromasa Yoshimoto, Daisaku.
HIGH TECHNOLGY FOR NAVIGATION. THE COMPANY Starlight Italia is an Italian Company, founded in 2005, from skilled engineers.
On the Design, Construction and Operation of a Diffraction Rangefinder MS Thesis Presentation Gino Lopes A Thesis submitted to the Graduate Faculty of.
CY3236A- PIRMOTION: Pyroelectric Infrared (PIR) Motion Detection Evaluation Kit (EVK)
Automated Inspection Using Machine Vision
Active Display Robot System Using Ubiquitous Network Byung-Ju Yi Hanyang University.
Competence Centre on Information Extraction and Image Understanding for Earth Observation Matteo Soccorsi (1) and Mihai Datcu (1,2) A Complex GMRF for.
THE Reference in Traffic Video Detection Benjamin Schiereck, Sales Manger Traficon Germany Improving road and tunnel safety via incident management: implementing.
Real-Time Phase-Stamp Range Finder with Improved Accuracy Akira Kimachi Osaka Electro-Communication University Neyagawa, Osaka , Japan 1August.
1. This seminar paper is based upon the project work being carried out by the collaboration of Delphi- Delco Electronics (DDE) and General Motors Corporation.It.
Camera-based wildland fire detection: Lessons learnt Sharad C. Karmacharya Researcher Wildland Fire Operations Research Group FERIC Western Division Sharad.
CODAR Ben Kravitz September 29, Outline What is CODAR? Doppler shift Bragg scatter How CODAR works What CODAR can tell us.
Sensing for Robotics & Control – Remote Sensors R. R. Lindeke, Ph.D.
Emergency Position Indicating Radio Beacon
AUTOMATIC TARGET RECOGNITION OF CIVILIAN TARGETS September 28 th, 2004 Bala Lakshminarayanan.
Tests of AWAKE spectrometer screen and camera at PHIN Introduction Layout Procedure Setup, results (runs 1 – 5) Conclusions L. Deacon, S. Mazzoni, B. Biskup.
THAT’S RIGHT FOLKS.... MATH! Navigation Calculations.
UNITS OF DISTANCE AND SPEED Statute Mile is a distance of 5,280 Nautical Mile (6,080 feet) is the average length of one minute of latitude. Kilometer is.
Abstract Combines are used in fields to perform the complex operations necessary to effectively harvest crops. The swath width detection system would assist.
Aperture & Shutter Speed Digital Photography. Aperture Also called the f-stop Refers to the adjustable opening in an optical instrument, such as a camera.
1. 2 Types of Ambushes ♦ Offensive ● Infantry ● Special Operations (Snatch&Go, priority targets) ● Armored ● Artillery ♦ Defensive Actions ● Defend roads,
Camera LENSES, APERTURE AND DEPTH OF FIELD. Camera Lenses Wide angle lenses distort the image so that extreme wide angle can look like its convex such.
CNSA,, Date Nov Coordination Group for Meteorological Satellites - CGMS The Status of current and future CNSA Earth Observing System Presented.
Distance Measuring Equipment (DME)
Distance Measuring Equipment (DME)
RVP vision probe for REVO-2. Non-contact measurement Surface finish 5-axis scanning and touch 2D scanning and 3D touch 3D scanning and touch The REVO-2.
Camera Settings What Do They Do?. Opening in the camera that controls the amount of light that reaches the image sensor Aperture.
Best Practice T-Scan5 Version T-Scan 5 vs. TS50-A PropertiesTS50-AT-Scan 5 Range51 – 119mm (stand- off 80mm / total 68mm) 94 – 194mm (stand-off.
Tobias Kohoutek Institute of Geodesy and Photogrammetry Geodetic Metrology and Engineering Geodesy ANALYSIS AND PROCESSING OF 3D-IMAGE-DATA FOR ROBOT MONITORING.
TOUCHLESS TOUCHSCREEN USER INTERFACE
Objective: To use probability calculations to determine the chance of success of a Search and Rescue mission Probability lesson SaRprobability.lgfl.net.
Advanced Camera Handling I
RESEARCH TRAINING VESSEL OF GDYNIA MARITIME UNIVERSITY
VEMANA INSTITUTE OF TECHNOLOGY,BANGALORE
Camera Settings What Do They Do?.
Automatic Speed Control Using Distance Measurement By Single Camera
Creative Camera Techniques
Why Box Cameras are still Cool?
Forecasting Drifting Objects
Range gated cameras Lynx series.
War Field Spying Robot with Night Vision Wireless Camera
Night Vision Technology
From: The perceptual basis of common photographic practice
THE OIL SEA HARVESTER SYSTEM :
Waves, Optics & Motion Test
Light 24 GHz Multi-Channel RADAR System Aiding Unmanned Aerial Vehicle Navigation Soumyaroop Nandi.
Proof of Concept Testing
Kinect for Creative Development with open source frameworks
Expanding Square Search Pattern
Depth Of Field (DOF).
Depth Of Field.
Presentation transcript:

DETECTION OF SURVIVORS USING THERMO & NIGHT VISION SYSTEM (UNDER DEVELOPMENT) Zbigniew Burciu, Teresa Abramowicz-Gerigk, Piotr Michna, Leszek Smolarek, Jarosław Soliwoda, Andrzej Szklarski, Sebastian Ukleja Gdynia Maritime University – Poland Technologies for Search, Assistance and Rescue Le Quartz Brest, France Presented by Sebastian Ukleja

Detection of survivors using Thermo & Night Vision System Stage 1 – Thermo vision as a sensor Stage 2 – Designing a system Stage 3 – Trials at sea Stages of research

Detection of survivors using Thermo & Night Vision System 10 persons – 20 minutes later 4,4°C 10 persons – just after manning -3,2°C

Detection of survivors using Thermo & Night Vision System Distance: 0,5 nautical mile Distance: 0,6 nautical mile Trials at sea Trials at sea Life raft

Detection of survivors using Thermo & Night Vision System Searching during night time Searching during night time Thermo vision as a sensor for SAR action Improved detection Improved detection Life rafts with survivors or not Life rafts with survivors or not

Detection of survivors using Thermo & Night Vision System Phase 2 – Where to install? Phase 3 – Compensation of ship motion Phase 4 – Selecting parts of equipment Phase 5 – Automatic detection Phase 1 – System in outline Stage 2 – Designing a system

Detection of survivors using Thermo & Night Vision System Computer system for analysing images Sensors: thermo vision and night vision camera with stroboscope laser illuminator Special device to reduce effect of ship’s motion Special device to reduce effect of ship’s motion Monitor and control panel on the bridge Monitor and control panel on the bridge Phase 1 – System in outline

Detection of survivors using Thermo & Night Vision System Phase 2 – Where to install? Phase 3 – Compensation of ship motion Phase 4 – Selecting parts of equipment Phase 5 – Automatic detection Phase 1 – System in outline Stage 2 – Designing a system

Length: 56,34 m Breadth: 11,36 m Speed: 12 knots Built in Poland in year 2000 The prototype of our system was installed on m/s Horyzont II Phase 2 – Where to install? Detection of survivors using Thermo & Night Vision System

Phase 2 – Where to install? The best place to install: Maximize field of vision Maximize field of vision Reduce effect of temperature form funnel Reduce effect of temperature form funnel Reduce effect of ship’s motions Reduce effect of ship’s motions Detection of survivors using Thermo & Night Vision System

Phase 2 – Where to install? Point 3 Point 3 - smallest effect of ship motions

Detection of survivors using Thermo & Night Vision System Phase 2 – Where to install? Phase 3 – Compensation of ship motion Phase 4 – Selecting parts of equipment Phase 5 – Automatic detection Phase 1 – System in outline Stage 2 – Designing a system

Detection of survivors using Thermo & Night Vision System Phase 3 – Compensation of ship motion

Detection of survivors using Thermo & Night Vision System Scanning speed versus ship movement for δ = 3 0 for δ = 1 0 Calm sea

Detection of survivors using Thermo & Night Vision System δ = 3 0 δ = 1 0 Rough sea Scanning speed versus ship movement

Detection of survivors using Thermo & Night Vision System Phase 2 – Where to install? Phase 3 – Compensation of ship motion Phase 4 – Selecting parts of equipment Phase 5 – Automatic detection Phase 1 – System in outline Stage 2 – Designing a system

Detection of survivors using Thermo & Night Vision System Atmosphere Lens Matrix Camera Object Background Phase 4 – Selecting parts of equipment

Detection of survivors using Thermo & Night Vision System Phase 4 – Selecting parts of equipment  Т  (3  5)  С for uncovered human body  Т  (3  5)  С for uncovered human body Range 2 km - focal length about 300 mm. Range 2 km - focal length about 300 mm. We have chosen focal length 240 mm We have chosen focal length 240 mm RANGERANGE  Т [  С] [km] 2,27 km 1,82 km 0,76 km

Detection of survivors using Thermo & Night Vision System Phase 2 – Where to install? Phase 3 – Compensation of ship motion Phase 4 – Selecting parts of equipment Phase 5 – Automatic detection Phase 1 – System in outline Stage 2 – Designing a system

Detection of survivors using Thermo & Night Vision System Phase 5 – Automatic detection Integration of detection hits Extraction Program uses: Computer system for analyzing images CFAR processing (constant false-alarm rate )

Detection of survivors using Thermo & Night Vision System After CFAR 2 life rafts, distance  0,8 nautical mile, focal length = 100mm Phase 5 – Automatic detection

Detection of survivors using Thermo & Night Vision System 2 life rafts, distance  0,8 nautical mile, focal length = 100mm CFAR & integration Phase 5 – Automatic detection

Detection of survivors using Thermo & Night Vision System Distance 0,25 nautical mile Distance 0,25 nautical mile CFAR Phase 5 – Automatic detection

Detection of survivors using Thermo & Night Vision System CFAR&integration Distance 0,25 nautical mile Distance 0,25 nautical mile Phase 5 – Automatic detection

Stage 3 – Trials at sea Detection of survivors using Thermo & Night Vision System

Stage 3 – Trials at sea Detection of survivors using Thermo & Night Vision System

Search object – 25 life raft with 6 person in Helly-Hansen and RIB rescue boat as assistance DISTANCE 1,35 Nm Detection of survivors using Thermo & Night Vision System

Search object – 25 life raft with 6 person in Helly-Hansen and RIB rescue boat as assistance DISTANCE 2,22 Nm Detection of survivors using Thermo & Night Vision System

Search object – 25 life raft with 6 person in Helly-Hansen and RIB rescue boat as assistance DISTANCE 2,58 Nm Detection of survivors using Thermo & Night Vision System

Search object – 25 life raft with 6 person in Helly-Hansen and RIB rescue boat as assistance DISTANCE 2,76 Nm Detection of survivors using Thermo & Night Vision System

The movie...

Detection of survivors using Thermo & Night Vision System Bearing information Thermo vision Control panel Night vision

Conclusions: Detection of survivors using Thermo & Night Vision System Search during the night People in life raft Automatic detection Further work: Make final tests of automatic detection Determine sweep width and POD Determine effect of rain and fog Computer aided system for search object identification

Thank you for attention Detection of survivors using Thermo & Night Vision System

Sweep width Probability of Detection Detection of survivors using thermo-noktovision system