03-10-2012, 03:48 PM
Smart Camera
Smart Camera.pdf (Size: 469.97 KB / Downloads: 106)
Abstract
Smart cameras are cameras that can perform tasks far beyond simply taking photos and recording videos. Thanks to the purposely built-in intelligent image processing and pattern recognition algorithms, smart cameras can detect motion, measure objects, read vehicle number plates, and even recognize human behaviors. They are essential components to build active and automated control systems for many applications, and they will play significant role in our daily life in the near future. This paper aims to provide a first comprehensive review of smart camera technologies and applications. Here, we analyse the reasons behind the recent rapid growth of the smart cameras, discuss different categories of them and review their system architectures. We also examine their intelligent algorithms, features and applications. Finally we conclude with a discussion on design issues, challenges and future technological directions.
Keywords: smart cameras, pattern recognition, machine vision, computer vision, video surveillance, embedded systems.
Introduction
What is a smart camera? Different researchers and camera manufacturers offer different definitions. There does not seem to be a well-established and agreed-upon definition in either the video surveillance or machine vision industries, probably the two most active and advanced applications for smart cameras at present. For the purpose of this paper, we define a smart camera as a vision system in which the primary function is to produce a high-level understanding of the imaged scene and generate application-
captures video of a scene, detects motion in the region of interest, and raises an alarm when the detected motion satisfies certain criteria. In this case, the ASIP is motion detection and alarm generation.
The Rapid Growth of Smart Cameras
Coming of Age of CMOS Image Sensors
The advent of CMOS image sensors (CIS) in late 1990s played an important role in the development of smart camera technology and systems, and has potential to make smart camera smaller, cheaper and more pervasive. Compared to CCD, CIS have several advantages which make them excellent candidates for smart camera front-end. These include smaller size, cheaper manufacturing cost, lower power consumption, the ability to build a camera-on-a-chip, the ability to integrate intelligent processing circuits onto the sensor chip, and significantly simplified camera system design.
Research in Computer Vision and Pattern Recognition
What makes a camera smart is the intelligent ASIP - the application-specific information processor built into the camera system. The advancement in academic and industrial research in real-time image processing and understanding, pattern recognition, machine learning, computer vision and video communication continues to provide a large library of intelligent algorithms for use by smart cameras for different applications. As an example, Intel’s OpenCV (Open Source Computer Vision) Library [3] has been very popular with academic researchers and students working on smart camera projects. Every year, numerous international journals, conferences and workshops give researchers world-wide forums to present their innovative work in areas such as computer vision and pattern recognition. A lot of the work presented can be seen as embryos of future smart cameras. Recently, first ever international conferences and workshops have been held focusing on the design of embedded vision systems.
Socio-Economical Drivers
Thanks to Moore’s law, semiconductor chips and computer hardware continue to shrink in size, reduce in cost and gain in performance. This has driven the prices of cameras, frame grabbers and computers down and made smart camera systems, especially PC-based systems, more affordable to research and development on one hand and to the market and end-users on the other. As hardware constraints (cost-wise) are lifted, software developers have more freedom to write "smarter" algorithms.
One of the most significant developments in surveillance and security industries in the last several years has been the wide use of CCTV (Closed Circuit Television) cameras and their impact on crime, terrorist attacks, and on the general public. It is noticeable that after the 9/11 event in the US, video surveillance has received more attention not only from the academic community
Digital Video Surveillance
The first generation of CCTV cameras (1980s-1990s) was mostly analog cameras with limited functionality and high cost. Digital CCTV cameras and the use of DVR (Digital Video Recorders) represented the second generation (2G, 1990s-now). Digital CCTV cameras built using CCD and CMOS image sensors provide better video quality, some intelligent functions such as motion detection, electronic PTZ (Pan-Tilt-Zooming), and networking. The 2G CCTV systems have become mass market products, fuelled by improved affordability and society’s increasing concerns over safety and security. According to estimates made in 2004 by market research firm Datamonitor [5], digital video surveillance is a high-growth segment within the overall surveillance market estimated at 55% CAGR (Compound Annual Growth Rate) between 2003 and 2007. In dollar terms, between 2003 and 2007 the market will grow from US$1.3bn to US$7.4bn globally.
However, the 2G CCTV systems are not “smart” enough to help prevent crimes or terror attacks, even though they proved very useful in post-event identification of crime perpetrators. The 2G CCTV systems are mostly not automated systems and rely strongly on trained security personnel to perform image analysis, object tracking and identification. The increasing number of cameras makes this difficult for real-time analysis by security personnel. Network bandwidth is another important issue affecting real-time processing needed for crime prevention. The intelligent video surveillance system (IVSS) (also called the third generation CCTV system) will try to provide solutions to these problems. Smart cameras will be one of the fundamental building blocks of the IVSS, making it possible to build and deploy automated, distributed and intelligent multi-sensory surveillance systems capable of tracking humans and suspected objects, analyzing human behaviors, and etc. Many market research firms have predicted significant growth in intelligent video systems and smart cameras.
Smart Camera.pdf (Size: 469.97 KB / Downloads: 106)
Abstract
Smart cameras are cameras that can perform tasks far beyond simply taking photos and recording videos. Thanks to the purposely built-in intelligent image processing and pattern recognition algorithms, smart cameras can detect motion, measure objects, read vehicle number plates, and even recognize human behaviors. They are essential components to build active and automated control systems for many applications, and they will play significant role in our daily life in the near future. This paper aims to provide a first comprehensive review of smart camera technologies and applications. Here, we analyse the reasons behind the recent rapid growth of the smart cameras, discuss different categories of them and review their system architectures. We also examine their intelligent algorithms, features and applications. Finally we conclude with a discussion on design issues, challenges and future technological directions.
Keywords: smart cameras, pattern recognition, machine vision, computer vision, video surveillance, embedded systems.
Introduction
What is a smart camera? Different researchers and camera manufacturers offer different definitions. There does not seem to be a well-established and agreed-upon definition in either the video surveillance or machine vision industries, probably the two most active and advanced applications for smart cameras at present. For the purpose of this paper, we define a smart camera as a vision system in which the primary function is to produce a high-level understanding of the imaged scene and generate application-
captures video of a scene, detects motion in the region of interest, and raises an alarm when the detected motion satisfies certain criteria. In this case, the ASIP is motion detection and alarm generation.
The Rapid Growth of Smart Cameras
Coming of Age of CMOS Image Sensors
The advent of CMOS image sensors (CIS) in late 1990s played an important role in the development of smart camera technology and systems, and has potential to make smart camera smaller, cheaper and more pervasive. Compared to CCD, CIS have several advantages which make them excellent candidates for smart camera front-end. These include smaller size, cheaper manufacturing cost, lower power consumption, the ability to build a camera-on-a-chip, the ability to integrate intelligent processing circuits onto the sensor chip, and significantly simplified camera system design.
Research in Computer Vision and Pattern Recognition
What makes a camera smart is the intelligent ASIP - the application-specific information processor built into the camera system. The advancement in academic and industrial research in real-time image processing and understanding, pattern recognition, machine learning, computer vision and video communication continues to provide a large library of intelligent algorithms for use by smart cameras for different applications. As an example, Intel’s OpenCV (Open Source Computer Vision) Library [3] has been very popular with academic researchers and students working on smart camera projects. Every year, numerous international journals, conferences and workshops give researchers world-wide forums to present their innovative work in areas such as computer vision and pattern recognition. A lot of the work presented can be seen as embryos of future smart cameras. Recently, first ever international conferences and workshops have been held focusing on the design of embedded vision systems.
Socio-Economical Drivers
Thanks to Moore’s law, semiconductor chips and computer hardware continue to shrink in size, reduce in cost and gain in performance. This has driven the prices of cameras, frame grabbers and computers down and made smart camera systems, especially PC-based systems, more affordable to research and development on one hand and to the market and end-users on the other. As hardware constraints (cost-wise) are lifted, software developers have more freedom to write "smarter" algorithms.
One of the most significant developments in surveillance and security industries in the last several years has been the wide use of CCTV (Closed Circuit Television) cameras and their impact on crime, terrorist attacks, and on the general public. It is noticeable that after the 9/11 event in the US, video surveillance has received more attention not only from the academic community
Digital Video Surveillance
The first generation of CCTV cameras (1980s-1990s) was mostly analog cameras with limited functionality and high cost. Digital CCTV cameras and the use of DVR (Digital Video Recorders) represented the second generation (2G, 1990s-now). Digital CCTV cameras built using CCD and CMOS image sensors provide better video quality, some intelligent functions such as motion detection, electronic PTZ (Pan-Tilt-Zooming), and networking. The 2G CCTV systems have become mass market products, fuelled by improved affordability and society’s increasing concerns over safety and security. According to estimates made in 2004 by market research firm Datamonitor [5], digital video surveillance is a high-growth segment within the overall surveillance market estimated at 55% CAGR (Compound Annual Growth Rate) between 2003 and 2007. In dollar terms, between 2003 and 2007 the market will grow from US$1.3bn to US$7.4bn globally.
However, the 2G CCTV systems are not “smart” enough to help prevent crimes or terror attacks, even though they proved very useful in post-event identification of crime perpetrators. The 2G CCTV systems are mostly not automated systems and rely strongly on trained security personnel to perform image analysis, object tracking and identification. The increasing number of cameras makes this difficult for real-time analysis by security personnel. Network bandwidth is another important issue affecting real-time processing needed for crime prevention. The intelligent video surveillance system (IVSS) (also called the third generation CCTV system) will try to provide solutions to these problems. Smart cameras will be one of the fundamental building blocks of the IVSS, making it possible to build and deploy automated, distributed and intelligent multi-sensory surveillance systems capable of tracking humans and suspected objects, analyzing human behaviors, and etc. Many market research firms have predicted significant growth in intelligent video systems and smart cameras.