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The mechanism behind collisions between vehicles and pedestrians must be thoroughly studied in order to prevent future traffic accidents. In particular, preventing collisions where pedestrian steps out onto the road from behind an obstruction such as buildings, walls or vehicles is a challenging problem. To tackle this problem, we propose situation dependent topic model (SDTM), a regression model...
To develop a safe Intelligent Transportation System (ITS) while driving on unpredictable curves or road regions, high precision road segmentation and cover level of forward view estimation for drivers is necessary. Cover level of forward view is defined as the level of difficulty in predicting the dangerousness of road edge or incoming object near road edge especially at a curve due to the obstacles...
We propose a novel method for seamline determination based on semantic segmentation for aerial image mosaicking. First, we train a convolutional neural network (CNN) for pixel labeling to extract building regions. Using the trained CNN, we create a building probability map from an input aerial image with no pre-processing. We then use Dijkstra’s algorithm to find the optimal seamline as a shortest...
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