• Journal of Information Processing Systems
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• v.19 no.4
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• pp.439-449
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• 2023

This paper deals with a resource efficient artificial intelligence (AI) service architecture for multi-channel video streams. As an AI service, we consider the object detection model, which is the most representative for video applications. Since most object detection models are basically designed for a single channel video stream, the utilization of the additional resource for multi-channel video stream processing is inevitable. Therefore, we propose a resource efficient AI service framework, which can be associated with various AI service models. Our framework is designed based on the modular architecture, which consists of adaptive frame control (AFC) Manager, multiplexer (MUX), adaptive channel selector (ACS), and YOLO interface units. In order to run only a single YOLO process without regard to the number of channels, we propose a novel approach efficiently dealing with multi-channel input streams. Through the experiment, it is shown that the framework is capable of performing object detection service with minimum resource utilization even in the circumstance of multi-channel streams. In addition, each service can be guaranteed within a deadline.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.6
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• pp.1092-1098
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• 2002

This paper discusses the composition of the theory of reinforcement teaming, which is applied in real-time teaming, and evolutionary strategy, which proves its the superiority in the finding of the optimal solution at the off-line teaming method. The individuals are reduced in order to team the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations are proposed. It is possible to control the control object varied as time changes. As the state value of the control object is generated, applied evolutionary strategy each sampling time because of the teaming process of an estimation, selection, mutation in real-time. These algorithms can be applied, the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes. In the future, studies are needed on the proof of the theory through experiments and the characteristic considerations of the robustness against the outside disturbances.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.124-129
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• 2013

This paper proposes a high-performance vector inner product calculation circuit for real-time object recognition based on SVM algorithm. SVM algorithm shows a higher detection rate than other object recognition algorithms. However, it requires a huge amount of computational efforts. Since vector inner product calculation is one of the major operations of SVM algorithm, it is important to implement a high-performance vector inner product calculation circuit for real-time object recognition capability. The proposed circuit adopts the pipeline architecture with six stages to increase the operating speed and makes it possible to recognize objects in real time based on SVM. The proposed circuit was described in Verilog HDL at RTL. For silicon verification, an MPW chip was fabricated using TSMC 180nm standard cell library. The operation of the implemented MPW chip was verified on the test board with test application software developed for the chip verification.

• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1789-1804
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• 1999

This paper presents a simulation-based system for verification and validation(V&V) of design implication of the Visual Real-time Object Model which is produced by existing object's behavior design method. This system can simulate the dynamic interactions using the executable Ada simulation machine, and can detect various logical and temporal problems in the visual real-time object model prior to the real implementation of the application systems. Also, the system can generate the Ada prototype code from the validated specification. This system is implemented by Visual C++ version 4.2. For simulation, this system is using the Ada language because Ada's real-time expression capabilities such as concurrent processes, rendezvous, temporal behavior expression, and etc, are competent compared to other languages. This work contributes to a tightly coupling of methodology-based visual models and formal-based simulation systems, and also contributes to a realization of automated specification V&V.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2141-2155
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• 2020

In order to meet the requirements of background change, illumination variation, moving shadow interference and high accuracy in object detection of moving camera, and strive for real-time and high efficiency, this paper presents an object detection algorithm based on sparse approximation recursion and sparse coding migration in subspace. First, low-rank sparse decomposition is used to reduce the dimension of the data. Combining with dictionary sparse representation, the computational model is established by the recursive formula of sparse approximation with the video sequences taken as subspace sets. And the moving object is calculated by the background difference method, which effectively reduces the computational complexity and running time. According to the idea of sparse coding migration, the above operations are carried out in the down-sampling space to further reduce the requirements of computational complexity and memory storage, and this will be adapt to multi-scale target objects and overcome the impact of large anomaly areas. Finally, experiments are carried out on VDAO datasets containing 59 sets of videos. The experimental results show that the algorithm can detect moving object effectively in the moving camera with uniform speed, not only in terms of low computational complexity but also in terms of low storage requirements, so that our proposed algorithm is suitable for detection systems with high real-time requirements.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.285-288
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• 2017

In this paper, we propose a vision-based object detection and tracking system using online learning. The proposed system adopts a feature point-based method for tracking a series of inter-frame movement of a newly detected object, to estimate rapidly and toughness. At the same time, it trains the detector for the object being tracked online. Temporarily using the result of the failure detector to the object, it initializes the tracker back tracks to enable the robust tracking. In particular, it reduced the processing time by improving the method of updating the appearance models of the objects to increase the tracking performance of the system. Using a data set obtained in a variety of settings, we evaluate the performance of the proposed system in terms of processing time.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1990.10a
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• pp.23-27
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• 1990

A new signal processing system for real time displacement measurement in sinusoidal phase modulating interferometry is described. Although sinusoidal phase modulating interferometry is effective in measuring with high accuracy the displacement of an object, conventional signal processing takes a long time. In this method, detection of the object's displacement is easily achieved by sampling the interference signal at those times that satisfy certain conditions and by processing the sampled signals with electric circuits in real time. The delay time of this signal processing system is < 45${\mu}$s. Specially in this paper we describe all electronic circuit and optical system design

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1991.10a
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• pp.33-37
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• 1991

A now signal precessing system for real time displacement measurement in sinusoidal phase modulating interferometry is described. Although sinusoidal phase modulating interferometry is effective in measuring with high accuracy the displacement of an object, conventional signal processing takes along time. In this method, detection of the object's displacement is easily achieved by sampling the interference signal at those times that satisfy certain conditions and by processing the sampled signals with electric circuits in real time. the delay time of this signal processing system is < 45 $\mu$s. Specially in this paper we describe all electronic circuit and optical system design

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.177-179
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• 2005

This paper suggests a high-speed blurred blob image inspection algorithm. When we inspect some products using high-resolution camera, the detected blob images usually have severe blur. And the blur makes it hard to detect an object. There are many blur-processing algorithms, but most of them have no real-time property for high-speed applications at all. In this paper, an MMX technology based algorithm is suggested. The suggested algorithm was found to be effective to detect the blurred blob images via many simulations and long time real-plant experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.94.2-94
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• 2002

$\textbullet$ The method to have real-time response at the motion control. $\textbullet$ The trajectory generation method guarantees the continuous acceleration in changing the velocity during the actuator is moving. $\textbullet$ We propose the velocity profile generation algorithm in order to change object position or object velocity with continuous acceleration using blending method.