27-28 October 2011 Sofia, Bulgaria Future Internet Applications for Traffic Surveillance and Management APPLICATIONS OF VIDEO SURVEILLANCE SYSTEMS FOR TRAFFIC DATA ACQUISITION Author: Vasil Lakov

Applications of video surveillance systems for traffic data acquisition 1.Goals of traffic management 2.Types of traffic sensors 3.Video road sensors 4.Advantages of video sensors 5.Disadvantages of video sensors 6.Hardware enhancement methods 7.Software enhancement methods 8.Future of video road sensors 9.Conclusion 10.Examples Slide: 1 / 24 TOPICS

1.Goals of traffic management Slide: 2 / 24 Monitoring of: Road network utilization Rush hours Environmental pollution Travel times and delays Dangerous roads Traffic violations Control by: Adaptive road intersection New roads More parking space GPS traffic services Planning of public transport VMS signs Law enforcement Decisions: Road capacity Overall view of network Choosing best projects Exchanging traffic info Speed limits Applications of video surveillance systems for traffic data acquisition

2.Types of traffic sensors Slide: 3 / 24 In-vehicle sensors (route monitoring) Road sensors (point monitoring) Mobile phones GPS navigation RFID transponders Microwave radars Laser scanners Ultrasound scanners Audible sound sensors Infrared cameras Normal CCTV cameras Applications of video surveillance systems for traffic data acquisition

2.Types of traffic sensors Slide: 4 / 24 In-vehicle sensors ADVANTAGES COVER ENTIRE ROAD NETWORK TRAVEL TIME DATA NO NEED FOR INFRASTRUCTURE MOST DRIVERS HAVE GPS / PHONE Mobile phones location: Which phone to track? When to track it? Not so accurate! DIS ADVANTAGES DEVICE PRICE ENDANGERED PRIVACY REGISTRATION IN SYSTEM LARGE COUNT OF DEVICES NEEDED RFID NEED OVERHEAD READERS GPS DATA NEED DOWNLOADING TO SYSTEM Applications of video surveillance systems for traffic data acquisition

2.Types of traffic sensors Slide: 5 / 24 Road sensors ADVANTAGES PRIVACY IS GARANTEED SENSORS CAN BE REALOCATED POINT MONITORING SYSTEM DON’T ENGAGE PEOPLE NO TAXES AND NEW DEVICES CAN PROVIDE RICH TRAFFIC DATA DIS ADVANTAGES NEED FOR INFRASTRUCTURE SYSTEM NEED LARGE COUNT OF SENSORS SOME SENSORS ARE FIXED blue zone – microwave red zone – passive infrared green zone – ultrasonic Applications of video surveillance systems for traffic data acquisition

3.Video road sensors Slide: 6 / 24 System architecture: Centralized Distributed Hybrid System parts: Video cameras Communication network Computers + software Operation: Video frames processing with computer/machine vision techniques Applications of video surveillance systems for traffic data acquisition

3.Video road sensors Slide: 7 / 24 Automatic traffic data collecting and watching Only watching Centralized system: Easy upgrading of functions Standard cameras Existing cameras Distributed system: Low speed connection Less complex computers More expensive cameras Applications of video surveillance systems for traffic data acquisition

4.Advantages of video sensors Slide: 8 / 24 Video road sensors are good choice for traffic surveillance because: Using existing CCTV networks Using existing control centers Covering many road lanes Covering long road sections Capable of detecting traffic violations and incidents Relocatable traffic sensors Possibility for adding new functions Provide video signal without additional devices Applications of video surveillance systems for traffic data acquisition

4.Advantages of video sensors Slide: 9 / 24 All this means that video sensors are: Cheap solution Universal solution for many traffic projects Shorter time for deployment Technology with long life cycle Adaptable solution to every customer Additional video sensors features: Easy installation Simple maintenance IT systems integration Applications of video surveillance systems for traffic data acquisition

5.Disadvantages of video sensors Slide: 10 / 24 The difficulties come from video frames processing. There are 3 sources for sub-optimal results: Low light and bad weather conditions Scene complexity Low quality of video frames Low light and bad weather: Night time Heavy rain and snow Thick fog and mist Light reflection Scene complexity: Camera position and orientation Various moving objects Buildings, trees, structures Low quality: Camera lens Image sensor Low resolution Blurry image Applications of video surveillance systems for traffic data acquisition

5.Disadvantages of video sensors Slide: 11 / 24 Low light and bad weather: Objects detection Vehicles missed Vehicle classification Vehicle identification Scene complexity: Merging of adjacent cars Counting people and objects False alarms for violations Mixing different traffic flows Low quality: Video frame distortion Incorrect traffic params Unstable frame quality and parameters Applications of video surveillance systems for traffic data acquisition

6.Hardware enhancement methods Slide: 12 / 24 Hardware ways for better image quality precede software frame processing stage! For best results it is necessary to: Choose appropriate camera installation place Choose special camera for the traffic monitoring Configure camera functions for best performance Use optical filters Applications of video surveillance systems for traffic data acquisition

6.Hardware enhancement methods Slide: 13 / 24 Camera place: High place (pole, traffic light) > 10 m Road-side building On the median, center of roadbed or close to road Tilted down, towards the road, without sky Shooting receding traffic if height is small Camera characteristics: Stationary camera Zoom is not necessary Progressive scan matrix Camera lens with bigger aperture Optical image stabilization Applications of video surveillance systems for traffic data acquisition

6.Hardware enhancement methods Slide: 14 / 24 Camera functions: Back Light Compensation― Automatic White Balance― Automatic Focus― Automatic Iris― Automatic Gain Control + Automatic Electronic Shutter + Optical filters: Ultraviolet cut filter Polarized filter UV filter reduces haziness created by ultraviolet light. Polarizing filter stops the light with a particular direction of polarisation. This reduces oblique reflections and can saturate the image. Additional video parameters: Gamma correction Brightness correction Contrast correction Applications of video surveillance systems for traffic data acquisition

7.Software enhancement methods Slide: 15 / 24 After we have excellent video quality, we can write the software (Actual sensor, retrieving traffic data). Software stage include: Foreground object detection (identification) / Background evaluation Object filtering ! Vehicle filtering ! Measuring vehicle parameters Vehicle classification Checking for violations and accidents Applications 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 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 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 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 acquisition

Slide: 20 / 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 acquisition

Slide: 21 / 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 acquisition

Slide: 22 / 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 acquisition

Slide: 23 / 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 acquisition

Future Internet Applications for Traffic Surveillance and Management Thank you for your attention! The road ahead! Slide: 24 / 24 Vasil Lakov APPLICATIONS OF VIDEO SURVEILLANCE SYSTEMS FOR TRAFFIC DATA ACQUISITION