Complexity Analysis of Vision Functions for Comparison of Wireless Smart Cameras

There are a number of challenges caused by the large amount of data and limited resources such as memory, processing capability, energy consumption, and bandwidth, when implementing vision systems on wireless smart cameras using embedded platforms. It is usual for research in this field to focus on the development of a specific solution for a particular problem. There is a requirement for a tool which facilitates the complexity estimation and comparison of wireless smart camera systems in order to develop efficient generic solutions. To develop such a tool, we have presented, in this paper, a complexity model by using a system taxonomy. In this model, we have investigated the arithmetic complexity and memory requirements of vision functions with the help of system taxonomy. To demonstrate the use of the proposed model, a number of actual systems are analyzed in a case study. The complexity model, together with system taxonomy, is used for the complexity estimation of vision functions and for a comparison of vision systems. After comparison, the systems are evaluated for implementation on a single generic architecture. The proposed approach will assist researchers in benchmarking and will assist in proposing efficient generic solutions for the same class of problems with reduced design and development costs.

[1]  Najeem Lawal,et al.  Complexity analysis of vision functions for implementation of wireless smart cameras using system taxonomy , 2012, Real-Time Image and Video Processing.

[2]  Kang G. Shin,et al.  Real-time dynamic voltage scaling for low-power embedded operating systems , 2001, SOSP.

[3]  Senyo Apewokin,et al.  Efficiently mapping high-performance early vision algorithms onto multicore embedded platforms , 2009 .

[4]  Mohamed ElHelw,et al.  WASP: Wireless autonomous sensor prototype for Visual Sensor Networks , 2010, 2010 IFIP Wireless Days.

[5]  Bernhard Rinner,et al.  Resource-Aware Coverage and Task Assignment in Visual Sensor Networks , 2011, IEEE Transactions on Circuits and Systems for Video Technology.

[6]  Ming-Ting Sun,et al.  Resource-Efficient FPGA Architecture and Implementation of Hough Transform , 2012, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[7]  Stephan Hengstler.  Stereo Vision in Smart Camera Networks , 2008 .

[8]  Roberto Manduchi,et al.  Energy Consumption Tradeoffs in Visual Sensor Networks , 2006 .

[9]  Wayne H. Wolf,et al.  Design and implementation of ubiquitous smart cameras , 2006, IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (SUTC'06).

[10]  Hamid K. Aghajan,et al.  Application-Oriented Design of Smart Camera Networks , 2007, 2007 First ACM/IEEE International Conference on Distributed Smart Cameras.

[11]  Michele Magno,et al.  A low-power wireless video sensor node for distributed object detection , 2007, Journal of Real-Time Image Processing.

[12]  Bernhard Rinner,et al.  The evolution from single to pervasive smart cameras , 2008, 2008 Second ACM/IEEE International Conference on Distributed Smart Cameras.

[13]  Nael B. Abu-Ghazaleh,et al.  A taxonomy of wireless micro-sensor network models , 2002, MOCO.

[14]  G. Blake,et al.  A survey of multicore processors , 2009, IEEE Signal Processing Magazine.

[15]  Najeem Lawal,et al.  Exploration of Tasks Partitioning between Hardware Software and Locality for a Wireless Camera Based Vision Sensor Node , 2011, 2011 Sixth International Symposium on Parallel Computing in Electrical Engineering.

[16]  Deborah Estrin,et al.  Cyclops: in situ image sensing and interpretation in wireless sensor networks , 2005, SenSys '05.

[17]  Reinaldo A. C. Bianchi,et al.  Implementing Computer Vision Algorithms in Hardware: An FPGA/VHDL-Based Vision System for a Mobile Robot , 2001, RoboCup.

[18]  Alexander Hornberg.  Handbook of Machine Vision , 2006 .

[19]  Bernhard Rinner,et al.  Visual on-line learning in distributed camera networks , 2008, 2008 Second ACM/IEEE International Conference on Distributed Smart Cameras.

[20]  Najeem Lawal,et al.  Exploration of target architecture for a wireless camera based sensor node , 2010, NORCHIP 2010.

[21]  Eduardo de la Torre,et al.  Using SRAM Based FPGAs for Power-Aware High Performance Wireless Sensor Networks , 2012, Sensors.

[22]  Anil K. Jain,et al.  Computer Vision Algorithms on Reconfigurable Logic Arrays , 1999, IEEE Trans. Parallel Distributed Syst..

[23]  Najeem Lawal,et al.  Analysis and characterization of embedded vision systems for taxonomy formulation , 2013, Electronic Imaging.

[24]  Najeem Lawal,et al.  Implementation of Wireless Vision Sensor Node for Characterization of Particles in Fluids , 2012, IEEE Transactions on Circuits and Systems for Video Technology.

[25]  Alistair Armitage,et al.  Comparative Study on Connected Component Labeling Algorithms for Embedded Video Processing Systems , 2010, IPCV.