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Bi-i: A standalone ultra high speed cellular vision system

IEEE Circuits and Systems Magazine 2005年第2期5卷 36-45页

作者： Zarándy, Ákos Rekeczky, Csaba Analogical and Neural Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences Budapest Hungary Faculty of Information Technology Péter Pázmány Catholic University Budapest Hungary Analogic Computers Ltd. Budapest Hungary

The Bi-i standalone cellular vision system is introduced and discussed. In the first part, the underlying sensor and system level architectures are presented and various implementations are overviewed. This computing platform consists of state-of-the-art sensing, cellular-sensing-processing, digital signal processing and communication devices that make it possible to use the system as an ideal computing platform for combined topographic and non-topographic calculations in sensing-processing-actuation scenarios. In the second part of the paper, ultra-high frame rate laboratory experiments are shown and discussed to highlight the most peculiar features of the system and its applicability in various industrial quality control areas. The overview underlines the potentials of the Bi-i vision system for unmanned intelligent vehicle applications in visual exploration, identification, tracking and navigation. ©2005 IEEE.

关键词： Sensors

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Various implementations of topographic, sensory, cellular wave computers

Various implementations of topographic, sensory, cellular wa...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： A. Zarandy M. Foldesy P. Szolgay S. Tokes C. Rekeczky T. Roska MTA-SZTAKI Analogical and Neural Computing Laboratory Budapest Hungary

The cellular wave computer architecture, based on the CNN universal machine principle, has been implemented recently in many different physical forms. The mixed mode CMOS, the emulated digital (cell wise or as aggregated arrays), FPGA, DSP, as well as optical implementations are the main examples. In many cases, the sensory array is integrated as well. The new self contained unit, called Bi-i, winning the product of the year title at the Vision 2003 in Stuttgart as the fastest camera-computer, shows the application interest and impact being capable of sensing-computing with 50000 frames per second. In this paper a clear and concise comparison is presented between the various implementation modes.

关键词： Sensor arrays Optical sensors Computer architecture Sensor phenomena and characterization Optical arrays CMOS technology Physics computing Biomedical optical imaging Biology computing Optical feedback

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Programmable optical CNN implementation based on the template pixels' angular coding

Programmable optical CNN implementation based on the templat...

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IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： S.T. Kes L. Orzo T. Roska Analogical and Neural Computing Laboratory Hungarian Academy of Sciences Budapest Hungary

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Image matching based on co-motion statistics

Image matching based on co-motion statistics

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International Symposium on 3D Data Processing Visualization and Transmission

作者： Z. Szlavik L. Havasi T. Sziranyi Analogical and Neural Computing Laboratory Budapest Hungary Pazmany Peter Catholic University Budapest Hungary Analogical and Neural Computing Laboratory Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

This work presents a method for matching partially overlapping image-pairs where the object of interest is in motion, even if the motion is discontinuous and in an unstructured environment. In a typical outdoor multicamera surveillance system, an observed object as seen by separate cameras may appear very different, due to the variable influence of factors such as lighting conditions and camera angles. Thus static features such as object color, shape, and contours cannot be used for image matching. In this paper a different method is proposed for matching partially overlapping images captured by such cameras. The matching is achieved by calculation of co-motion statistics, followed by detection and rejection of points outside the overlap area and a nonlinear optimization process. The robust algorithm we describe finds point correspondences in two images without searching for any structures and without the need for tracking continuous motion. Trials using statistical motion-based image cross-registration, a robust rejection algorithm, and automatic 3D image-transformation and camera calibration on real-life outdoor images have demonstrated the feasibility of this approach.

关键词： Image matching Statistics Cameras Layout Calibration Humans Surveillance Shape Robustness Tracking

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A realistic mammalian retinal model implemented on complex cell CNN universal machine

A realistic mammalian retinal model implemented on complex c...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： D. Balya C. Rekeczky T. Roska Analogical & Neural Computing Laboratory Computer and Automation Research Institute Budapest Hungary

The visual system is probably the most important sensory modality for humans as well as for mammals. Its first and best-known part is the retina, which is not a mere photoreceptor or static camera but a sophisticated feature preprocessor with a continuous input and several parallel output channels. These channels build up a "visual language" and any realistic mammalian retina model should generate the elements of this visual language. The framework of mammalian retinal modeling via multi-layer CNN has been recently published. In the present paper we show the transformation of this model into a CNN-UM algorithm and the design steps of the implementation of this complex visual language. The analogic algorithm consists of a series of different complex-cell CNN dynamics. The algorithm is feasible on a recently fabricated complex cell CNN-UM chip. The decomposition method of the multilayer mammalian retina model will be discussed in detail.

关键词： Retina Cellular neural networks Turing machines Visual system Humans Photoreceptors Cameras Data preprocessing Algorithm design and analysis Heuristic algorithms

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Feature guided visual attention with topographic array processing and neural network-based classification

Feature guided visual attention with topographic array proce...

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International Joint Conference on neural Networks (IJCNN)

作者： G. Timar D. Balya I. Szatmari C. Rekeczky Analogical & Neural Computing Laboratory Computer and Automation Research Institute Budapest Hungary

Biological systems are constantly engulfed in sensory input that must be processed. Attention has evolved to cut down on the magnitude of the input and enable the agent to analyze the most important parts of the information. This is especially true for the visual system where the appropriate field of view and scale must be determined. Our system receives a video flow with considerably higher resolution than the resolution of the cellular neural net based visual microprocessor that computes the topographic features of the input. This process requires a dynamic positioning of the processing window in the video flow. We have developed a fast attention and selection algorithm that allows the system to choose the field of view and scale (zoom) level for the next frame based on the features computed from the current frame and the output of the ART or NNC-based classifiers. The algorithmic framework and hardware architecture of the system are presented along with experimental chip results for several video flows recorded in flying vehicles.

关键词： Array signal processing neural networks Biological systems Information analysis Visual system Cellular neural networks Microprocessors Vehicle dynamics Subspace constraints Hardware

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Detecting global spatial-temporal events: saccadic suppression

Detecting global spatial-temporal events: saccadic suppressi...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： D. Balya Analogical & Neural Computing Laboratory Computer and Automation Research Institute Budapest Hungary

You may think that while are watching a schema, your eyes move smoothly and continuously to investigate the circuitry, but that is not the case. Your eyes fixate on a part of the circuit hold for a moment then suddenly jump to a new position where a particular visual detail attracts your eyes. During this jump or saccade the eyes move rapidly and we hardly notice that, relative to our eye position, the entire visual world globally shifts. Vision is in some sense turned off during saccades, which is called saccadic suppression. This paper presents a neuromorphic algorithm to detect these spatial-temporal events from the input flow. The algorithm of the saccadic suppression event detection is implemented on the standard cellular nonlinear network universal machine environment. The processing time is roughly one millisecond on the ACE4k CNN-UM chip in the Aladdin environment, and therefore it can serve as a common function in any real-time spatial-temporal algorithm. The saccadic suppression event detector can be used in different areas such as video shot detection or to define the instant when the time-dependent part of the algorithm, e.g. homotopy, has to be initialized.

关键词： Event detection Eyes Change detection algorithms Lighting Retina Circuits Gunshot detection systems Layout Cameras Switches

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Fault tolerant CNN template design and optimization based on chip measurements

Fault tolerant CNN template design and optimization based on...

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IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： P. Foldesy L. Kek T. Roska A. Zarandy G. Bartfai Analogical and Neural Computing Laboratory Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

Proposes a generic method for finding non-propagating cellular neural network (CNN) templates that can be implemented reliably on a given CNN Universal Machine chip. The method has two main components: (i) adaptive optimization of templates based on measurements of actual CNN chips, (ii) simplification and decomposition of Boolean operators into a sequence of simpler ones that work correctly and more robustly on a given chip. Examples are presented using two stored-program CNNUM chips to demonstrate the effectiveness of the proposed method, whose advantages and limitations are also discussed.

关键词： Fault tolerance Cellular neural networks Design optimization Semiconductor device measurement Optimization methods Turing machines Robustness Neurons Very large scale integration Scattering parameters

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Analogic CNN computing: architectural, implementation, and algorithmic advances-a review

Analogic CNN computing: architectural, implementation, and a...

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IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： T. Roska Analogical and Neural Computing Laboratory Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

In this paper, first, an overview is given about the whole scenario of analogic cellular neural net (CNN) computing. Next, two areas of CNN computing technology are considered briefly: (i) the architectural advances, especially variable resolution and adaptation in space, time, and value and (ii) the computational infrastructure from high-level language and compiler to physical implementations. Three basic physical implementations are considered: analogic CMOS, emulated digital CMOS and optical. The computational infrastructure is the same for all implementations, except the physical interfaces.

关键词： Cellular neural networks Physics computing Cloning High level languages Image processing Space technology Application software Computer architecture Morphology Analog computers

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Supervised and unsupervised art-like classifications of binary vectors on the CNN universal machine

Supervised and unsupervised art-like classifications of bina...

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IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： D. Balya T. Roska Analogical & Neural Computing Laboratory Computer and Automation Research Institute Budapest Hungary

Fast and robust classification of feature vectors is a crucial task in a number of real-time systems. A cellular neural/nonlinear network universal machine (CNN-UM) can be applied very efficiently as a feature detector and also for post-processing the results for object recognition. This paper shows how a robust classification scheme based on adaptive resonance theory (ART) can also be mapped to the CNN-UM. The designed analogic CNN algorithm is capable of classifying the extracted binary feature vectors keeping the advantages of the ART networks. An analogic algorithm is presented for unsupervised classification with tunable sensitivity and automatic new class creation. Another CNN-UM algorithm is suggested for supervised classification. In addition to the two algorithms, a new "repair" function is proposed to reduce the number of the created classes. The presented binary feature vector classification is feasible on the existing standard CNN-UM chips.

关键词： Cellular neural networks Turing machines Robustness Subspace constraints Real time systems Cellular networks Computer vision Object detection Detectors Object recognition

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