smart camera for traffic surveillance
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02-07-2010, 10:41 PM

iam a 4th year engineering student,branch computer science.. 8th july iam having a seminar and presentation on the topic "smart camera for traffic surveillance".. i need the full report and a powerpoint presentation of this topic urgently...since it is on 8th i kindly request you to post the full report and ppt at the earliest...

thanking you...
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Joined: Sep 2010
08-10-2010, 10:54 AM

.ppt   ADARSH.ppt (Size: 688.32 KB / Downloads: 216)




Smart camera- integration of advanced image sensors and high performance processors.
Must be implemented as an embedded system.
Mounted in tunnels and aside highways.
Electric power supplied by power socket or solar panels.
Smart camera delivers better video quality and video analysis results.
Captures images and videos and processes them.
Transfers the video stream via a network.
Offer flexible video transmission.


Smart camera is comprised of
Processing unit
Communication unit
Sensor requirements
High dynamic range and little blur
High resolution
Maximum frame rate

CMOS sensor

Processing requirements
Video compression
Video analysis
Computation of traffic statistics
Camera control and firmware
Video compression
Video should be compressed.
Video analysis
Extracts an abstract scene from the raw data.
If any situation detected, alarm is triggered.
Computation of traffic statistics
Computed out of video stream.
Camera control and firmware
Control aperture and flash control and the firmware.
Communication requirements
Compressed video and video analysis are transferred to control station.
Besides data upload it should also support data download.
System requirements
Low power consumption
Low heat dissipation
Timing constraints should be correct.


Divided into three parts
Video sensor
Processing unit
Communication unit
Video sensor
First stage in overall data flow.
CMOS sensor is used.
Processing unit
Second stage in overall data flow.
Performance requirements are fulfilled with digital signal processors(DSP) which are loosely coupled.
Each processor connected to its own local memory.
DSP’s external memory capacity between 8mb and 256mb.
Communication unit
Final stage in overall data flow.
Processing unit transfers data to the communication unit via generic interface.
Flashes, pan-tilt zoom heads and dome are controlled by this unit.
Low power considerations
Dynamic power management(DPM)
Individual components can be switched to different power modes during runtime.
The commands to change the components’ power modes are issued by a central Power Manager (PM).
In order to decide which command to issue the PM must have knowledge about the system’s workload.
In the smart camera the PM is located in the OS kernel of the host DSP.
Characteristics are stored in look-up-tables in the PM and are used as input for the PMP.


The software architecture of the smart camera is basically divided into two parts:
DSP’s are configured basically to run computation tasks.
XScale processor is primarily used for system control and communication purposes.
Video compression
The advanced simple profile MPEG-4 encoding method is well-suited for traffic surveillance.
The smart camera uses HTTP to provide a flexible and user-friendly user interface.
UDP is used for multicast streaming-video transmission.
Network connection
Internet connections require the TCP/IP protocol implemented as an IP stack.
Uses protocols HTTP,FTP and UDP.
The smart camera’s firmware controls the overall system behavior, and provides interfaces and methods for different tasks .
Four basic run levels are defined by the firmware:
The normal mode
The alarm mode
The full update mode
The partial update mode
Normal mode
Video compression running quality is low.
Alarm mode
Enters this mode when an alarm mode is detected.
Quality of video stream is increased.
Full update mode
Used when the firmware is updated.
Partial update mode
Activated when a task has to be re-placed or removed from the smart camera.


Low power consumption.
Flexible video transmission.
Noise in the video data is reduced by video computation.
Less expensive.
Smart camera is fully integrated, simple and reliable.


Smart camera solutions are not flexible
Usually provide limited user interface.


Video motion detection
Detects a change in the video.
Built-in filters ignore camera vibrations and areas with constant motion.
User can define object properties and for some intrusion detection situations direction.

Static Object Detection

Offers the ability to analyze and track static (stationary) objects.
An advanced Non-isolated Object filter is useful in dynamic, congested settings.
Other applications are:
Motion analysis
Facial identification
Video surveillance for large complexes.
Video conferencing
Store/Business Surveillance - Theft Prevention/Curtailment
Door Entrance Monitoring/Video Intercoms
Observing unsupervised facility / factory.


Smart camera technology will begin to enter new applications.
Applications include
security and access control markets.
In the automotive industry.
For collision avoidance, and even one day – for the toy industry.
Even our automobiles may soon be outfitted with miniature eyes.


The smart camera integrates a CMOS image sensor, a processing unit featuring two high performance DSP’s and a network interface. It senses and analysis the video and transfers the computed information via network, thus managing the traffic effectively. Advances in performance and integration will enable new and more functionality implemented in smart camera.
seminar class
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25-02-2011, 10:53 AM

A Smart Camera for Traffic Surveillance
Abstract — The integration of advanced CMOS image sensors with high-performance
processors into an embedded system facilitates new application classes such as smart
cameras. A smart camera combines video sensing, video processing and communication
within a single device. This paper reports on the prototype implementation of
a smart camera for traffic surveillance. It captures a video stream, computes traffic
information and transfers the compressed video stream and the traffic information
to a network node. The achieved experimental results of the implemented stationary
vehicle detection demonstrate the feasibility of our approach.
1 Introduction
Due to their logarithmic behavior, high dynamic range and high bit resolution the low-cost
and low-powerCMOS sensors acquire images with the necessary quality for further image
processing under varying illumination conditions. The integration of these advanced image
sensors with high-performance processors into an embedded system facilitates new
application classes such as smart cameras. Smart cameras not only capture images or
video sequences, they further perform high-level image processing such as motion analysis
and face recognition on-board and transmit the (compressed) video data as well as the
extracted video information via a network.
An important application area where smart cameras can potentially and advantageously
replace most known cameras, frame grabbers and computer solutions is visual traffic
surveillance [1]. CMOS image sensors can overcome problems like large intensity contrasts
due to weather conditions or road lights and further blooming, which is an inherent
weakness of existing CCD image sensors. Furthermore, noise in the video data is reduced
by the capability of video computation “close” to the CMOS sensor. Thus, the smart
camera delivers a new video quality and better video analysis results, if it is compared
to existing solutions. Beside these qualitative arguments and from a system architecture
point of view, the smart camera is an important concept in future digital and heterogeneous
third generation visual surveillance systems [2]. Not only image enhancement and image
compression but also video computing algorithms for scene analysis and behavior understanding
are becoming increasingly important. These algorithms have a high demand for
real-time performance and memory. Fortunately, smart cameras can support these demand
as low-power, low-cost embedded systems with sufficient computing performance
and memory capacity. Furthermore, they offer flexible video transmission and computing
in scalable networks with thousands of cameras through a fully digital interface.
The purpose of this paper is to present first results of an ongoing research project and implimentation between
ARC Seibersdorf research, the Institute for Technical Informatics at Graz University
of Technology and the pattern recognition and image processing group at Vienna
University of Technology. The primary goal of this project and implimentation is the development of a smart
camera for traffic surveillance. This paper presents the camera’s prototype implementation
and a case study of our smart camera concept with respect to stationary vehicle
detection in tunnels. We chose this application, because it is by far the most important
application (80 percent of all applications) in traffic surveillance.
The remainder of the paper is organized as follows: Section 2 presents the requirements
of a smart camera and lists the related work. The hardware architecture is outlined in
Section 3, while the software components required by the smart camera are depicted in
Section 4. Experiments and a prototype description is described in Section 5. Section 6
concludes this paper with a short discussion.
2 Requirements and Related Work
2.1 Requirements of a Smart Camera

In general a smart camera is compromised of a sensor, a processing and a communication
unit. In this section we briefly discuss the requirements for each of these units as well as
some system wide requirements.
2.1.1 Sensor Requirements
The image sensor is the prime input for a smart camera. An appropriate image quality is,
therefore, essential for the performance of the entire system.
Dynamic Range Traffic surveillance applications enforce high demands on the image
sensor. Typical traffic situations may contain a high dynamics, e.g., when high-intensity
areas, such as the high-beam of a vehicle, appear concurrently with low-intensity areas
such as the car’s silhouette at night. Image sensors with high dynamic range and little
blur are preferred for these applications. Additionally, high dynamic-range sensors ease
the design of the camera control and the control of the lens aperture in changing light

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14-03-2012, 12:58 PM

sir, i need full seminar and presentation report on "smart camera for traffic surveillance".. please make it as soon as possible..

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