Performance Analysis of Hardware/Software Middleware in Network of Smart Camera Systems

Mefenza

2015

J Real-Time Image Proc

Self Cite

In this work, a clustering approach for bandwidth reduction in distributed smart camera networks is presented. Properties of the environment such as camera positions and environment pathways, as well as dynamics and features of targets are used to limit the flood of messages in the network. To better understand the correlation between camera positioning and pathways in the scene on one hand and temporal and spatial properties of targets on the other hand, and to devise a sound messaging infrastructure, a unifying probabilistic modeling for object association across multiple cameras with disjointed view is used. Communication is efficiently handled using a taskoriented node clustering that partition the network in different groups according to the pathway among cameras, and the appearance and temporal behavior of targets. We propose a novel asynchronous event exchange strategy to handle sporadic messages generated by non-frequent tasks in a distributed tracking application. Using a Xilinx-FPGA with embedded Microblaze processor, we could show that, with limited resource and speed, the embedded processor was able to sustain a high communication load, while performing complex image processing computations.

Section: Discussionmentioning

confidence: 95%

Section: System Prototypingmentioning

confidence: 99%

Section: Communicationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Efficient network clustering for traffic reduction in embedded smart camera networks

Zarezadeh¹,

Mefenza

2015

J Real-Time Image Proc

Self Cite

“…We used this approach in the design of a FPGA-based embedded smart camera platform [1] and proved superior results compared to existing embedded smart camera systems. Also, in our previous works [2], [3], we proposed a software/hardware co-design middleware approach, called Hardware ORB for low latency intercommunication with deterministic behavior among the smart camera nodes in a Distributed Smart Camera (DSC) setup. The middleware enables developers to program distributed applications seamlessly, without having to focus on the details of the implementation, thus reducing the development time [4].…”

Section: Introductionmentioning

confidence: 99%

Enabling communication infrastructure and protocol on embedded distributed smart cameras

Zarezadeh

2011 Fifth ACM/IEEE International Conference on Distributed Smart Cameras

2011

Self Cite

We present a viable communication infrastructure and protocols to support the versatile data exchange in a network of smart cameras. Each node in network is an embedded smart camera whose hardware/software architecture was carefully designed to meet the performance requirement while providing sufficient flexibility. We introduce a novel scalable clustering approach, which uses asynchronous event exchange among the neighboring camera nodes. The new software-based event exchange structure is integrated into a Hardware Object Request Broker (ORB), which guarantees the real-time performance for transmission in and the seamless design of the network. The empirical results from case studies prove the viability of the proposed event exchange for a set of FPGA-based embedded smart cameras.

Hardware Middleware for Person Tracking on Embedded Distributed Smart Cameras

Zarezadeh

International Journal of Reconfigurable Computing

2012

Self Cite

Tracking individuals is a prominent application in such domains like surveillance or smart environments. This paper provides a development of a multiple camera setup with jointed view that observes moving persons in a site. It focuses on a geometrybased approach to establish correspondence among different views. The expensive computational parts of the tracker are hardware accelerated via a novel system-on-chip (SoC) design. In conjunction with this vision application, a hardware object request broker (ORB) middleware is presented as the underlying communication system. The hardware ORB provides a hardware/software architecture to achieve real-time intercommunication among multiple smart cameras. Via a probing mechanism, a performance analysis is performed to measure network latencies, that is, time traversing the TCP/IP stack, in both software and hardware ORB approaches on the same smart camera platform. The empirical results show that using the proposed hardware ORB as client and server in separate smart camera nodes will considerably reduce the network latency up to 100 times compared to the software ORB.