Utsushi Sakai

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This paper presents a novel real-time pedestrian detection system utilizing a LIDAR-based object detector and convolutional neural network (CNN)-based image classifier. Our method achieves over 10 frames/second processing speed by constraining the search space using the range information from the LIDAR. The image region candidates detected by the LIDAR are(More)
This paper proposes a camera-based visibility estimation method for a traffic sign. The visibility here indicates how a visual target is easy to be detected and recognized by a human driver (not a machine). This research aims at realizing a nuisance-free driver assistance system which sorts out information depending on the visibility of a visual target, in(More)
A bipolar electrode was stereotaxically implanted in or near the medial forebrain bundle at the level of the posterior lateral hypothalamus of male albino Wistar-Imamichi rats. 1) Two electrode sites implanted in a rat both in the lateral hypothalamus and in the dorsal noradrenaline bundle supported self-stimulation (SS) behavior. 2) Methamphetamine(More)
In recent years, demand for pedestrian detection using inexpensive low-resolution LIDAR (LIght Detection And Ranging) is increasing, as it can be used to prevent traffic accidents involving pedestrians. However, it is difficult to detect pedestrians from a low-resolution (sparse) point-cloud obtained by a low-resolution LIDAR. In this paper, we propose(More)
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