The Experts below are selected from a list of 318 Experts worldwide ranked by ideXlab platform
Ajith K. Kumar - One of the best experts on this subject based on the ideXlab platform.
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AVSS - Color-Based Signal Light Tracking in Real-Time Video
2006 IEEE International Conference on Video and Signal Based Surveillance, 2006Co-Authors: Mahipal Reddy Yelal, Sreela Sasi, Glenn R. Shaffer, Ajith K. KumarAbstract:Tracking or detecting the position and color of Signal Lights has an important role in transport industry. Auto detection of Signal Light colors and their position using computer vision techniques provides or acts as a proof against a fraudulent claim losses. The current technology, such as vehicle mounted recording system, provides event recognition videos and the cause behind an accident. But it does not provide the complete information about color associated with Signal Lights. The detection of the color of a Signal Light under different illuminations is a critical issue. In this research, an intelligent method for tracking color of Signal Lights using La*b* color model combined with contour tracking is proposed. This research finds application in transportation, law enforcement and insurance claims. The system increases the efficiency of the accident investigation process and reduces the economic loss associated with automobile accidents of all types.
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Color-Based Signal Light Tracking in Real-Time Video
2006 IEEE International Conference on Video and Signal Based Surveillance, 2006Co-Authors: Mahipal Reddy Yelal, Sreela Sasi, Glenn R. Shaffer, Ajith K. KumarAbstract:Tracking or detecting the position and color of Signal Lights has an important role in transport industry. Auto detection of Signal Light colors and their position using computer vision techniques provides or acts as a proof against a fraudulent claim losses. The current technology, such as vehicle mounted recording system, provides event recognition videos and the cause behind an accident. But it does not provide the complete information about color associated with Signal Lights. The detection of the color of a Signal Light under different illuminations is a critical issue. In this research, an intelligent method for tracking color of Signal Lights using La*b* color model combined with contour tracking is proposed. This research finds application in transportation, law enforcement and insurance claims. The system increases the efficiency of the accident investigation process and reduces the economic loss associated with automobile accidents of all types.
Yousik Hong - One of the best experts on this subject based on the ideXlab platform.
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FUZZ-IEEE - The optimization of traffic Signal Light using artificial intelligence
10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297), 2001Co-Authors: Jeongjin Kang, Yousik HongAbstract:In the past, when there were few vehicles on the road, the TOD (time of day) traffic Signal worked very well. The TOD Signal operates on a preset Signal cycling which cycles on the basis of the average number of average passenger cars in the memory device of an electric Signal unit. Nowadays, with increasing vehicles on restricted roads, the conventional traffic Light creates prove startup-delay time and end-lag-time. The conventional traffic Light loses the function of optimal cycle, so 30-45% of the conventional traffic cycle is not matched to the present traffic cycle. We propose an electrosensitive traffic Light using a fuzzy look up table method which will reduce the average vehicle waiting time and improve average vehicle speed. Computer simulation results prove that reducing the average vehicle waiting time is better than than fixed Signal method which doesn't consider vehicle length.
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The optimization of traffic Signal Light using artificial intelligence
10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297), 2001Co-Authors: Jeongjin Kang, Yousik HongAbstract:In the past, when there were few vehicles on the road, the TOD (time of day) traffic Signal worked very well. The TOD Signal operates on a preset Signal cycling which cycles on the basis of the average number of average passenger cars in the memory device of an electric Signal unit. Nowadays, with increasing vehicles on restricted roads, the conventional traffic Light creates prove startup-delay time and end-lag-time. The conventional traffic Light loses the function of optimal cycle, so 30-45% of the conventional traffic cycle is not matched to the present traffic cycle. We propose an electrosensitive traffic Light using a fuzzy look up table method which will reduce the average vehicle waiting time and improve average vehicle speed. Computer simulation results prove that reducing the average vehicle waiting time is better than than fixed Signal method which doesn't consider vehicle length.
Mahipal Reddy Yelal - One of the best experts on this subject based on the ideXlab platform.
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AVSS - Color-Based Signal Light Tracking in Real-Time Video
2006 IEEE International Conference on Video and Signal Based Surveillance, 2006Co-Authors: Mahipal Reddy Yelal, Sreela Sasi, Glenn R. Shaffer, Ajith K. KumarAbstract:Tracking or detecting the position and color of Signal Lights has an important role in transport industry. Auto detection of Signal Light colors and their position using computer vision techniques provides or acts as a proof against a fraudulent claim losses. The current technology, such as vehicle mounted recording system, provides event recognition videos and the cause behind an accident. But it does not provide the complete information about color associated with Signal Lights. The detection of the color of a Signal Light under different illuminations is a critical issue. In this research, an intelligent method for tracking color of Signal Lights using La*b* color model combined with contour tracking is proposed. This research finds application in transportation, law enforcement and insurance claims. The system increases the efficiency of the accident investigation process and reduces the economic loss associated with automobile accidents of all types.
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Color-Based Signal Light Tracking in Real-Time Video
2006 IEEE International Conference on Video and Signal Based Surveillance, 2006Co-Authors: Mahipal Reddy Yelal, Sreela Sasi, Glenn R. Shaffer, Ajith K. KumarAbstract:Tracking or detecting the position and color of Signal Lights has an important role in transport industry. Auto detection of Signal Light colors and their position using computer vision techniques provides or acts as a proof against a fraudulent claim losses. The current technology, such as vehicle mounted recording system, provides event recognition videos and the cause behind an accident. But it does not provide the complete information about color associated with Signal Lights. The detection of the color of a Signal Light under different illuminations is a critical issue. In this research, an intelligent method for tracking color of Signal Lights using La*b* color model combined with contour tracking is proposed. This research finds application in transportation, law enforcement and insurance claims. The system increases the efficiency of the accident investigation process and reduces the economic loss associated with automobile accidents of all types.
D.c. Chin - One of the best experts on this subject based on the ideXlab platform.
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A model-free approach to optimal Signal Light timing for system-wide traffic control
Proceedings of 1994 33rd IEEE Conference on Decision and Control, 1994Co-Authors: J.c. Spall, D.c. ChinAbstract:A long-standing problem in traffic engineering is to optimize the flow of vehicles through a given road network. Improving the timing of the traffic Signals at intersections in the network is generally the most powerful and cost-effective means of achieving this goal. However, because of the many complex aspects of a traffic system-human behavioral considerations, vehicle flow interactions within the network, weather effects, traffic accidents, long-term (e.g., seasonal) variation, etc.-it has been notoriously difficult to determine the optimal Signal Light timing. This is especially the case on a system-wide (multiple intersection) basis. Much of this difficulty has stemmed from the need to build extremely complex open-loop models of the traffic dynamics as a component of the control strategy. This paper presents a fundamentally different approach for optimal Light timing that eliminates the need for such an open-loop model. The approach is based on a neural network (or other function approximator) serving as the basis for the control law, with the weight estimation occurring in closed-loop mode via the simultaneous perturbation stochastic approximation (SPSA) algorithm. Since the SPSA algorithm requires only loss function measurements (no gradients of the loss function), there is no open-loop model required for the weight estimation. The approach is illustrated by simulation on a six-intersection network with moderate congestion and stochastic, nonlinear effects.
H. Tsuchiya - One of the best experts on this subject based on the ideXlab platform.
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Broad-range tunable wavelength conversion of high-bit-rate Signals using super structure grating distributed Bragg reflector lasers
IEEE Journal of Quantum Electronics, 1996Co-Authors: H. Yasaka, H. Ishii, K. Takahata, K. Oe, Y. Yoshikuni, H. TsuchiyaAbstract:Tunable wavelength conversion of a 10 Gb/s Signal over a broad wavelength range of about 90 nm is achieved by using a super structure grating distributed Bragg reflector laser. The extinction ratio dependence of converted Signal Light on input Signal Light power and bias current to the laser active region is discussed. The extinction ratio becomes large when the input Signal Light power increases and the bias current decreases. Bit error rate measurements show that error-free, penalty-free wavelength conversion is achieved when the extinction ratio is large (12.5 dB) and that the bit rate which error-free wavelength conversion is possible increases as the input Signal Light power increases. Twenty Gb/s Signal wavelength conversion is also demonstrated.