27-28 October 27-28 October 2011 Sofia, 2011 Sofia, Bulgaria Bulgaria Future Internet Applications for Traffic Surveillance and Future Internet Applications for Traffic Surveillance and Management Management APPLICATIONS OF VIDEO SURVEILLANCE APPLICATIONS OF VIDEO SURVEILLANCE SYSTEMS FOR TRAFFIC DATA ACQUISITION SYSTEMS FOR TRAFFIC DATA ACQUISITION Author: Author: Vasil Lakov Vasil Lakov e- e- mail: mail: [email protected][email protected]
Transcript
27-28 October 2011 27-28 October 2011 Sofia, BulgariaSofia, Bulgaria
Future Internet Applications for Traffic Surveillance and ManagementFuture Internet Applications for Traffic Surveillance and Management
APPLICATIONS OF VIDEO SURVEILLANCE APPLICATIONS OF VIDEO SURVEILLANCE SYSTEMS FOR TRAFFIC DATA ACQUISITIONSYSTEMS FOR TRAFFIC DATA ACQUISITION
Applications of video surveillance systems for traffic data acquisitionApplications of video surveillance systems for traffic data acquisition
7. Software enhancement methods
Slide: 16 / 24
Machine vision is very powerful tool for video object detection. There are many methods and algorithms for this task. Some of them are more or less affected by image quality, vehicle occlusions and other factors.
For getting accurate traffic data, it is necessary to do two-stage data filtering. First stage include video frame filtering and second stage filters measured objects parameters. Only after this stage we can count and classify vehicle and check for violations!
Filtering and vehicle properties calculating tasks need some parameters to be set up. This is done automatically or manually in the beginning.
Such parameters can be:
Camera height and lens focal length
Road section length, number and borders of lanes
Real world - video coordinates calibration (2D -> 3D)
Threshold values for image binarization, speed limits
ROIs, maximum length and height of vehicles
And many others, depending on algorithms used
Applications of video surveillance systems for traffic data acquisitionApplications of video surveillance systems for traffic data acquisition
7. Software enhancement methods
Slide: 17 / 24
Video filtering:
Frame – Background Binarized difference Real vehicle detected
Real vehicle properties change slightly between two video frames:
Size
Shape
Speed
Direction
Location
Applications of video surveillance systems for traffic data acquisitionApplications of video surveillance systems for traffic data acquisition
8. Future of the video road sensors
Slide: 18 / 24
Development of video road sensors has to be in the direction of solving two base problems: vehicle occlusions and shadow merging and night time working.
Occlusions and shadows can be passed over by applying 3D scene recognition with stereoscopic cameras or by calculating object alignment from single 2D video frame.
Working during the night can be improved by using more sensitive image sensors in the camera, electronically and digitally intensifying video frames, using infrared projector or by developing new image analyzing algorithms.
Applications of video surveillance systems for traffic data acquisitionApplications of video surveillance systems for traffic data acquisition
9. Conclusion
Slide: 19 / 24
Perfect video sensors have these hardware features:
Progressive scan camera
Optical image stabilization
Vary-focal lens
Fully corrected lens
Ultraviolet and polarized optical filters
DSP computer block and IP communication link
Perfect software features:
Constant and on-demand video streaming
Memory for on-site data storing
Remote update of software
Two-stage data filtering
Applications of video surveillance systems for traffic data acquisitionApplications of video surveillance systems for traffic data acquisition
Slide: 20 / 24
10.Examples
Good position for the camera,
but the intersection is large!
(there are many vehicle flows)
Set region of interest (ROI) in the video frame – only road and vehicles
Applications of video surveillance systems for traffic data acquisitionApplications of video surveillance systems for traffic data acquisition
Slide: 21 / 24
10.Examples
Bad combination:
Night time
Wet road
Head lights reflections! (counting head lights is not good)
No shadows,
but the road is white not dark!
During bad weather the traffic slows down and traffic management gets really important!
Applications of video surveillance systems for traffic data acquisitionApplications of video surveillance systems for traffic data acquisition
Slide: 22 / 24
10.Examples
Night time:
Wrong place
Low quality image
Many unwanted objects
Single camera – the whole city
Megapixel camera
Separate small subzones
Camera installed on skyscraper
Applications of video surveillance systems for traffic data acquisitionApplications of video surveillance systems for traffic data acquisition
Slide: 23 / 24
10.Examples
Intersection monitoring
Tracking vehicles and pedestrians (danger situation - car on crossing)
Detection and classification of objects
(features tracking – without occlusion)
Applications of video surveillance systems for traffic data acquisitionApplications of video surveillance systems for traffic data acquisition
Future Internet Applications for Traffic Surveillance and ManagementFuture Internet Applications for Traffic Surveillance and Management
Thank you for your attention!Thank you for your attention!
