Deep Neural Network (DNN) is widely used for computer vision tasks, such as image classification, object detection, and segmentation. DNN accelerator on FPGA and especially Convolutional Neural Network (CNN) is a hot topic. More research and education should be conducted to boost this field. A starting point is required to make it easy for new entrants to join this field. We believe that FPGA-based Autonomous Driving (AD) motor cars are suitable for this because DNN accelerators can be used for image processing with low latency. In this paper, we propose an FPGA-based simple and open-source mini motor car system named RVCar with a RISC-V soft processor and a CNN accelerator. RVCar is suitable for the new entrants who want to learn the implementation of a CNN accelerator and the surrounding system. The motor car consists of Xilinx Nexys A7 board and simple parts. All modules except the CNN accelerator are implemented in Verilog HDL and SystemVerilog. The CNN accelerator is converted from a PyTorch model by our tool. The accelerator is written in C++, synthesizable by Vitis HLS, and an easy-to-customize baseline for the new entrants. FreeRTOS is used to implement AD algorithms and executed on the RISC-V soft processor. It helps the users to develop the AD algorithms efficiently. We conduct a case study of the simple AD task we define. Although the task is simple, it is difficult to achieve without image recognition. We confirm that RVCar can recognize objects and make correct decisions based on the results.

In recent years, much research interest has developed in image enhancement and haze removal techniques. With increasing demand for real time enhancement and haze removal, the need for efficient architecture incorporating both haze removal and enhancement is necessary. In this paper, we propose an architecture supporting both real-time Retinex-based image enhancement and haze removal, using a single module. Efficiently leveraging the similarity between Retinex-based image enhancement and haze removal algorithms, we have successfully proposed an architecture supporting both using a single module. The implementation results reveal that just 1% logic circuits overhead is required to support Retinex-based image enhancement in single mode and haze removal based on Retinex model. This reduction in computation complexity by using a single module reduces the processing and memory implications especially in mobile consumer electronics, as opposed to implementing them individually using different modules. Furthermore, we utilize image enhancement for transmission map estimation instead of soft matting, thereby avoiding further computation complexity which would affect our goal of realizing high frame-rate real time processing. Our FPGA implementation, operating at an optimum frequency of 125MHz with 5.67M total block memory bit size, supports WUXGA (1,920×1,200) 60fps as well as 1080p60 color input. Our proposed design is competitive with existing state-of-the-art designs. Our proposal is tailored to enhance consumer electronic such as on-board cameras, active surveillance intrusion detection systems, autonomous cars, mobile streaming systems and robotics with low processing and memory requirements.

Recently, the growing concepts that information communication technologies apply to social infrastructures have caused deep interests with wireless sensor networks (WSNs). WSNs can be used for various application areas such as home, health, factory and so on. For the different application areas, there are different technical issues (e.g., security, reliability, real time gathering, long life time, scalability). Efficient information gathering can be potentially obtained if we take a suitable information gathering method with considering the requirements of each WSN application. Thus, we have not persisted all information gathering perfectly and have proposed one of simple information gathering methods in response to the requirements of WSN applications in this paper. In the proposed method, the information is converted to physical-layer parameters of wireless communications, such as frequency and time. Also, simulations are performed to validate the effectiveness of the proposed method in real time gathering and estimating with high precision.

Shadow mapping is an efficient method to generate shadows in real time computer graphics and has broad variations from hard to soft shadow synthesis. Soft shadowing based on shadow mapping is a blurring technique on a shadow map or on screen space. Blurring on screen space has an advantage for efficient sampling on a shadow map, since the blurred target array has exactly the same coordinates as the screen. However, a previous blurring method on screen space has a drawback: the generated shadow is not correct when a view direction has a large angle to the normal of the shadowed plane. In this paper, we introduce a new screen space based method for soft shadowing that is fast and generates soft shadows more accurately than the previous screen space soft shadow mapping method. The resultant images show shadows produced by our method just stand in the same place, while shadows by the previous method change in terms of penumbra while the view moves. Surprisingly, although our method is more complex than the previous method, the measurement results of the calculation time show our method is almost the same performance. This is because it controls the blurring area more accurately and thus successfully reduces multiplications for blurring.

In this paper, we introduce layered low-density generator matrix (Layered-LDGM) codes for super high definition (SHD) scalable video systems. The layered-LDGM codes maintain the correspondence relationship of each layer from the encoder side to the decoder side. This resulting structure supports partial decoding. Furthermore, the proposed layered-LDGM codes create highly efficient forward error correcting (FEC) data by considering the relationship between each scalable component. Therefore, the proposed layered-LDGM codes raise the probability of restoring the important components. Simulations show that the proposed layered-LDGM codes offer better error resiliency than the existing method which creates FEC data for each scalable component independently. The proposed layered-LDGM codes support partial decoding and raise the probability of restoring the base component. These characteristics are very suitable for scalable video coding systems.

The steady approach of advanced nations toward realization of ubiquitous computing societies has given birth to rapidly growing demands for new-generation distributed computing (DC) applications. Consequently, economic and reliable construction of new-generation DC applications is currently a major issue faced by the software technology research community. What is needed is a new-generation DC software engineering technology which is at least multiple times more effective in constructing new-generation DC applications than the currently practiced technologies are. In particular, this author believes that a new-generation building-block (BB), which is much more advanced than the current-generation DC object that is a small extension of the object model embedded in languages C++, Java, and C#, is needed. Such a BB should enable systematic and economic construction of DC applications that are capable of taking critical actions with 100-microsecond-level or even 10-microsecond-level timing accuracy, fault tolerance, and security enforcement while being easily expandable and taking advantage of all sorts of network connectivity. Some directions considered worth pursuing for finding such BBs are discussed.

The EDD connection admission control scheme has been proposed for supporting real-time communication in packet-switched networks. In the scheme, when a connection establishment request occurs, the worst-case link delay in each link along the connection is calculated to determine whether the request can be accepted or not. In order to calculate the worst-case link delay, we must perform a check called the point schedulability check for each of some discrete time instants (checkpoints). Therefore when there are many checkpoints, the worst-case link delay calculation is time-consuming. We have proposed a high-speed calculation method. The method finds some checkpoints for which the point schedulability check need not be performed and removes such unnecessary checkpoints in advance before a connection establishment request occurs, and the check is performed for each of the remaining checkpoints after the request occurs. However, the method is not so effective under the situation that the maximum packet length in networks is large, because the method can find few unnecessary checkpoints under the situation. This paper proposes a new high-speed calculation method. We relax the condition which determines whether or not the point schedulability check need not be performed for each checkpoint in our previous method and derive a new condition for finding unnecessary checkpoints. Using the proposed method based on the new condition, we can increase the number of unnecessary checkpoints compared to our previous method. Numerical examples which are obtained by extensive simulation show that the proposed method can attain as much as about 50 times speedup.

The authors propose a system for searching the shape of human hands and fingers in real time and with high accuracy, without using any special peripheral equipment such as range sensor, PC cluster, etc., by a method of retrieving similar image quickly with high accuracy from a large volume of image database containing the complicated shapes and self-occlusions. In designing the system, we constructed a database in a way to be adaptable even to differences among individuals, and searched CG images of hand similar to unknown hand image, through extraction of characteristics using high-order local autocorrelational patterns, reduction of the amount of characteristics centering on principal component analysis, and prior rearrangement of data corresponding to the amount of characteristics. As a result of experiments, our system performed high-accuracy estimation of human hand shape where mean error was 7 degrees in finger joint angles, with the processing speed of 30 fps or over.

This paper presents a deformable fast computation elastic model for real-time processing applications. 'Gradational element resolution model' is introduced with fewer elements for fast computation, in which small elements are laid around the object surface and large elements are laid in the center of the object. Elastic element layout is changed dynamically according to the deformation of cutting or tearing objects. The element reconstruction procedure is applied little by little for each step of the recursive motion generation process to avoid an increase in motion computation time.

We have developed a two-dimensional flat-panel imager (FPI) utilizing conventional amorphous silicon (a-Si) thin film transistor (TFT) technology for AM-LCDs, and we have made a prototype. We can experimentally manufacture the FPI basically by utilizing conventional production lines of AM-LCDs, because the imager is based on the TFT array for AM-LCDs. The TFT performs both switching and photo-detecting functions itself. Using the FPI, we can capture monochrome images in real time, and can also achieve full-color images by introducing time-sequential driving based on a color backlight system with RGB-LEDs. The reliability of the TFT under bias and irradiation stress caused by capturing images is maintained by introducing an original driving method and processing the captured image. By making use of advantages the FPI has over conventional imaging systems, we hope that the FPI will be a useful compact imaging device for documents, pictures, fingerprints, and the like.

In this paper we present reconfigurable computing as a compelling choice of computing platform for real-time, onboard processing for satellite applications. In particular, we discuss the use of reconfigurable computing in the context of a real-time remote sensing system, providing motivation for such a system and describing attributes of reconfigurable computing that support it as the technology of choice. The High Performance Computing (HPC-I) payload, designed and developed for the Australian scientific satellite FedSat, is introduced as a demonstration of onboard processing in space using reconfigurable logic. We present an overview of the real-time remote sensing system architecture, and describe the design and implementation of three remote sensing algorithms in HPC-I for cloud masking, wildfire detection and volcanic plume detection. Finally, results from simulation and testing are presented which show very promising performance in terms of data throughput and detection capabilities.

The detection of timing constraint violation is crucial in reactive systems. A method of detecting deadline violation based on Floyd-Warshall shortest path algorithm has been proposed by Chodrow et al. We extend this method to detect the violation of minimum delay time in reactive systems where the repetition of event sequences frequently occurs.

We have developed a novel human facial tracking system that operates in real time at a video frame rate without needing any special hardware. The approach is based on the use of Lie algebra, and uses three-dimensional feature points on the targeted human face. It is assumed that the roughly estimated facial model (relative coordinates of the three-dimensional feature points) is known. First, the initial feature positions of the face are determined using a model fitting technique. Then, the tracking is operated by the following sequence: (1) capture the new video frame and render feature points to the image plane; (2) search for new positions of the feature points on the image plane; (3) get the Euclidean matrix from the moving vector and the three-dimensional information for the points; and (4) rotate and translate the feature points by using the Euclidean matrix, and render the new points on the image plane. The key algorithm of this tracker is to estimate the Euclidean matrix by using a least square technique based on Lie algebra. The resulting tracker performed very well on the task of tracking a human face.

In visual servoing, most studies are concerned with robotic application with known objects. In this paper, the problem of controlling a motion by visual servoing around an unknown object is addressed. In this case, the approach is interpreted as an initial step towards a perception goal of an unmodeled object. The main goal is to perform motion with regard to the object in order to discover several viewpoint of the object. An adaptive visual servoing scheme is proposed to perform such task. The originality of our work is based on the choice and extraction of visual features in accordance with motions to be performed. The notion of invariant feature is introduced to control the navigational task around the unknown object. During experimentation, a cartesian robot connected to a real time vision system is used. A CCD camera is mounted on the end effector of the robot. The experimental results present a linkage of desired motion around different kind of objects.

A management of WWW server is still relying on the expertise and heuristic of administrators, because the comprehensive understandings of server behavior are missing. The administrators should maintain the WWW server with good states that they should investigate the WWW server in real time. Therefore, it is exactly desirable to provide a measurement application that enables the WWW server administrators to monitor WWW servers in the actual operational environment. We developed a measurement application called ENMA (Enhanced Network Measurement Agent) which is specially designed for WWW server state analysis. Furthermore, we applied this application to the large scale WWW server operation to show its implementation and advantages. In this paper, we analyze the WWW server states based on precise monitoring of performance indices of WWW system to help the server management.

The development of saturation diving in civil and defense applications has enabled man to work in the sea at great depths and for long periods of time. This advance has resulted, in part, as a consequence of the substitution of helium for nitrogen in breathing gas mixtures. However, utilization of HeO2 breathing mixture at high ambient pressures has caused problems in speech communication; in turn, helium speech enhancement systems have been developed to improve diver communication. These speech unscramblers attempt to process variously the grossly unintelligible speech resulting from the effect of breathing mixtures and ambient pressure, and to reconstruct such signals in order to provide adequate voice communication. It is known that the glottal excitation is quasi-periodic and the vocal tract filter is quasi-stationary. Hence, it is possible to use an auto regressive modelisation to restore speech intelligibility in hyperbaric conditions. Corrections are made on the vocal tract transfer function, either in the frequency domain, or directly on the autocorrelation function. A spectral subtraction or noise reduction may be added to improve speech quality. A new VAD enhanced helium speech unscrambler is proposed for use in adverse conditions or in speech recognition. This system, implementable on single chip DSP of current technology, is capable to work in real time.

Most of current real time video retrieval systems use video transfer protocols such that servers simply transmit video packets in the same rate as clients play them. If any packets are corrupted during transmission, they will be lost and cannot be recovered by retransmission. In video retrieval systems, however, teh video data are stored in servers and clients can prefetch them prior to playing. So, it might be possible for the video retrieval systems to make corrupted video packets retransmitted before the play-out dead line. But the application of existing reliable protocols causes problems such that, if a packet does not arrive before the dead line due to retransmission, the packets following it will not be delivered to the upper layer even if they have already arrived. In this paper, we discuss how to apply reliable protocols to real time video retrieval systems and propose an new real time video transfer protocol over ATM network, which provides the video data prefetch, the flow control for video buffer, the selective retransmission with skipping function for video packets late for the play-out dead line, and the resynchronization function for video buffer. We have implemented an experimental system using our protocol and evaluated the performance. The results of performance evaluation shows that the proposed protocol decreases the number of unplayed video data largely when transmission errors are inserted in an ATM network.

The Guaranteed Bandwidth Protocol (GBW) is an access scheme being proposed for implementation of connection oriented services in DQDB networks. Connection oriented services are expected to handle both constant bit rate (CBR) and variable bit rate (VBR) traffic that have delay and jitter constraints. It has been reported that the GBW protocol can provide guaranteed bandwidth and lower delays compared to the ordinary DQDB protocol. However, the intensity of the jitter introduced by this scheme has not been made clear. This paper compares the jitter results for the GBW scheme to those obtained by a new access method called Modified Guaranteed Bandwidth (MOD_GBW) protocol, which is proposed here. It is shown through simulation that MOD_GBW also provides guaranteed bandwidth and that its delay and jitter characteristics are significantly better than those of the GBW protocol. In the simulation model, the DQDB stations are divided into two groups: 1)Real-Time (RT) stations that generate either CBR or VBR real-time traffic; and 2)Data stations that generate memoryless type of traffic. Data stations operate according to the ordinary DQDB protocol only. The main performance measure adopted here for the real-time traffic is the interdeparture time distribution of consecutive segments from an RT-station. We define the variance of this distribution as jitter. This paper also shows the impact of GBW/MOD_GBW on the performance of the data stations by evaluating their throughput and average bus access delay. Finally, we show that the network performance is weakly related to the number of RT-stations under MOD_GBW, but it depends strongly on the overall loading.

In order to display complicated virtual spaces in real time, such as spaces consisting of a dynamic natural scenery, we earlier proposed a method for simplifying the shape data of 3-D trees whereby the amount of shape data is efficiently reduced. The method generates tree shapes based on a fractal model according to the required level of details (LOD). By using a texture-mapping technique, we experimentally showed that our method can display 3-D tree images with allowable image quality in real time. However, methods for controlling the LOD of 3-D tree shapes in virtual spaces have yet to be discussed. In this paper, quantitative evaluations were made on the effect of a data simplification method employing such visual properties as resolution difference between the central vision and peripheral vision. Results showed that it is possible to display a complicated scene containing many trees in real time by controlling the LOD of tree shapes in the virtual space considering such visual properties. Furthermore, so that reality can be added to the virtual space, we consider that it is important to display the natural sways of wind-blown trees and plants in real time. Therefore, we propose a method for generating sway data for simplified tree shape data based on a simple physical model, in which each branch is connected to several other branches by springs, and also a new texture-mapping technique for rendering simplified tree shapes, making it appear as if the shapes have a high LOD. Finally, we show some examples of images of trees generated in real time by using our method, in which many trees exist and sway due to wind.

In this paper, we formulate and solve a discrete-time queueing problem that has two potential applications: ATM multiplexers and DQDB networks. We first consider the modeling of an ATM multiplexer. The object of the analysis is a periodic traffic stream (CBR traffic), which is one of the inputs to the multiplexer. As in previous works of the subject, we consider a memoryless background traffic input. Here, in addition to this background traffic, we take into account the influence of a high-priority traffic, which is time-correlated and requires expedited service. We analyze the influence of these two types of traffic on the statistics of the interdeparture time (jitter process) and the delay of the periodic traffic stream. We obtain their distributions in a form of z-transforms, and from these we derive closed form expressions for the average delay and the variance of the interdeparture time. Our results show that the delay and jitter are very sensitive to the burstiness of the high priority traffic arrival process. We next apply our analytical modeling to a DQDB network when some of its stations are driven by CBR sources. We can obtain interesting results concerning the influence of the physical location of a DQDB station on the jitter.