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Visually estimating a robot's own motion has been an active field of research within the last years. Though impressive results have been reported, some application areas still exhibit huge challenges. Especially for car-like robots in urban environments even the most robust estimation techniques fail due to a vast portion of independently moving objects. Hence, we move one step further and propose...
Vision systems are nowadays very promising for many on-board vehicles perception functionalities, like obstacles detection/recognition and ego-localization. In this paper, we present a 3D visual odometric method that uses a stereo-vision system to estimate the 3D ego-motion of a vehicle in outdoor road conditions. In order to run in real-time, the studied technique is sparse meaning that it makes...
We present a method for extracting ground and other planes from a single non rotating laser mounted on a slow moving car used for on-road driving. A laser scan is decomposed into linear clusters. Corresponding clusters from subsequent scans are merged to form planes. The ground plane is identified based on the current vehicle height and the variance in height of the planes. Once these seed planes...
This paper reports the advancement of a research extension. The outcome is a device installed in a long-haul bus for daily operation. The incumbent system features the combination of lane departure warning (LDW) function and forward collision warning (FCW) function employing the support vector machine (SVM) as the classifier. LDW recognizes the environment as in daytime or in nighttime by detecting...
In this paper, we present a new feature to model a class of events that consist of complex interactions among multiple entities captured by tracks and inter-object relationships over space and time. Existing approaches represent these events using features that measure only pairwise relationships between entities at a time, such as relative distance and relative speed. Due to the limitations of the...
In surveillance applications, search space reduction (SSR) is an essential element to efficient algorithms. In this study, spatial and temporal SSRs are integrated for license plate detection in video sequences; the plates could be extracted robustly and extremely fast. Our method started from spatial SSR by a bi-level one-pass plate extraction (BOPE) algorithm developed to extract plates accurately...
Vehicle tracking is a challenging problem in Intelligent Transport System. This paper presents a vehicle tracking approach combining blob based tracking and feature based tracking. First objects are detected as blobs using codebook(CB) algorithm and scale invariant feature transform(SIFT) features are extracted from the blobs. Then vehicles are tracked by using SIFT to match the vehicles frame-by-frame...
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