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Over the past years, automatic traffic accident detection (ATAD) based on video has become one of the most promising applications in intelligent transportation and is playing a more and more important role in ensuring travel safety. This paper proposes a classifier-based supervised method by viewing the last seconds before motor vehicle collisions as the detection target. In our method, we devise...
As an application of image recognition, special vehicle recognition is very important in military field. This paper proposes a deep-transfer model (DTM) to overcome the problems in existing recognition methods. The DTM combines deep-learning and transfer-learning to solve the difficulty in training deep model with insufficient simples, improving the performance of the recognition algorithm. At last,...
The goal of the project is to design intelligent and robust image-processing and augmented-reality algorithms for driver assistance and enhanced vehicular safety. In particular, the focuses were two-fold: (1) realizing the abilities to identify and localize in a vehicle''s on-board video the sweeping windshield wipers during raining days and (2) designing and implementing an in-painting technique...
This paper proposes a new algorithm to eliminate the wiper interference in a vehicle's onboard video to improve the detection rate of vision-based Advanced Driver Assistance Systems (ADAS), such as Forward Collision Warning (FCW) Systems. During raining days, the windshield wipers periodically and partially block the appearance of obstacles on the road that are to be detected in these early warning...
Advanced warning system for vehicles is a critical issue in recent years for automobiles, especially when the number of vehicles is growing rapidly world wide. The cost down of general cameras makes it feasible to have an intelligent system of visual-based event detection in front for forward collision avoidance and mitigation. When driving at nighttime, vehicles in front are generally visible by...
This paper presents a novel approach for retrieving images from databases using eigen color and the concept of multiple instance learning. Usually, vehicles have various colors and shapes under different viewpoints, weathers, and lighting conditions. All the variations will increase many difficulties and challenges in selecting a general feature to describe vehicles. Thus, traditional methods to retrieve...
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