Yoshikatsu Kimura

Experimental on Hierarchical Transmission Scheme for Visible Light Communication using LED Traffic Light and High-Speed Camera

LEDs are expected as lighting sources for next generation, and data transmission system using LEDs attract attention. In this paper, we present hierarchical coding scheme using LED traffic lights and high-speed camera for intelligent transport systems (ITS) application. Further, if each of LEDs in traffic lights is individually modulated, parallel data transmissions are possible using a camera as a reception device. Such parallel LED-camera channel can be modeled as spatial low-pass filtered channel of which the cut-off frequency varies according to the distance. To overcome, we propose hierarchical coding scheme based on 2D fast Haar wavelet transform. As results, the proposed hierarchical transmission schemes outperform the conventional on-off keying and the reception of high priority data is guaranteed even LED-camera distance is further.

On-vehicle receiver for distant visible light road-to-vehicle communication

In this paper, we propose a road-to-vehicle visible communication system for ITS. In this system, a LED traffic light is used as transmitter and a photodiode is used as receiver. There are several problems associated with applying visible light communication to the field of ITS. It is necessary to receive information from long distance. And tracking the transmitter for a certain moving distance of the vehicle is also important. We applied an imaging optics to receive information over long distance, and two cameras are used to solve the relationship between the transmitter and the receiver position changes with time, and vibrational correction technique is also fixed to the system to minimize vibrational affections. We developed algorithms to track the transmitter. The experiments were conducted to confirm the proposals.

Visible light road-to-vehicle communication using high-speed camera

We have been proposing visible light road-to-vehicle communication at intersection, using LED traffic light as the transmitter and on-vehicle high-speed camera as the receiver. Visible light communication is a wireless communication method using luminance, transmitting data by emitting light. Thus when we use image sensor as the receiver, detection of the transmitter is required to enable the communication. In this paper, we propose transmitter detection algorithm supposed that the sequence is captured at 1000 fps. We also made experiments to verify our algorithm, using the sequence captured by a high-speed camera fixed on a vehicle which is running at 30 km/h.

Pedestrian detection and direction estimation by cascade detector with multi-classifiers utilizing feature interaction descriptor

This paper proposes a pedestrian detection and direction estimation method by the cascade approach with multiclassifiers using the Feature Interaction Descriptor (FIND). FIND describes the high-level properties of an objects appearance by computing pair-wise interactions of adjacent regionlevel features. To perform efficient and accurate detection using FIND, we employ the cascade approach with multiclassifiers specialized in both the direction of a pedestrian and the distance of the pedestrian from a camera. Using this framework, the developed system can improve the detection performance and provide information of the direction of a pedestrian simultaneously. The experimental results show that superior detection performance and direction estimation results were obtained by our method.

Detection of LED traffic light by image processing for visible light communication system

We propose a visible light road-to-vehicle communication system at intersection for ITS. In this system, the communication between vehicle and a LED traffic light is approached using LED traffic light as the transmitter, and on-vehicle high-speed camera as the receiver. The LEDs in the transmitter are emitted with 500Hz and the images of those emitting LEDs are captured by a high-speed camera for conducting communication. In this communication, it is extremely necessary to find the transmitter and detect it for consecutive frames while vehicle is moving. In this paper, we introduce proposals for finding and detecting it for consecutive frames by image processing. Experimental results using appropriate images showed the effectiveness of the proposal.

Edge-Based Tracking of an LED Traffic Light for a Road-to-Vehicle Visible Light Communication System

We propose a visible light road-to-vehicle communication system at intersection as one of ITS technique. In this system, the communication between vehicle and a LED traffic light is approached using LED traffic light as a transmitter, and on-vehicle high-speed camera as a receiver. The LEDs in the transmitter are emitted in 500Hz and those emitting LEDs are captured by a high-speed camera for making communication. Here, the luminance value of each LED in the transmitter should be found for consecutive frames to achieve effective communication. For this purpose, first the transmitter should be identified, then it should be tracked for consecutive frames while the vehicle is moving, by processing the images from the high-speed camera. In our previous work, the transmitter was identified by getting the subtraction of two consecutive frames. In this paper, we mainly introduce an algorithm to track the identified transmitter in consecutive frames. Experimental results using appropriate images showed the effectiveness of the proposal.

Texture-based objects recognition for vehicle environment perception using a multiband camera

The vision-based intelligent vehicle systems for environment perception have required integration of image data acquired from multiple cameras. We developed multiband camera, which can simultaneously obtain both images of visible color and near infrared. In this paper, we present a texture-based objects recognition under road environment scene using a multiband image. The new color feature is proposed to cluster meaningful regions of a multiband image and the texture segmentation is utilized in classification of texture-based objects. Experimental results show that the proposed method effectively recognizes the texture-based objects including roads, buildings, trees, and sky, as well as faces of pedestrians. In the future, by integrating the shape-based objects recognition, which includes pedestrians, cars, and bicycles with texture-based objects recognition, the proposed system can expand into a complex scene understanding system for vehicle environment perception.