Chuanxiang Li

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Road marking is a key visual cue for driving in structured environments like highways and urban roads. Road marking detection plays an important role in advanced driver assistant systems and autonomous driving. Robust road marking detection is challenging for the variation of road scenes, the degradation of the markings and the changes of the illumination.(More)
To achieve better performance of visual tracking, an improved TLD tracking algorithm was proposed. Firstly, the performance of objects detection classifiers was improved by the usage of the color attributes of objects. The accuracy of objects detector was boosted by using the color attributes of initial object, which was labeled manually. Secondly, Kalman(More)
Lane detection is crucial part of vision driver assistance system of intelligent vehicles. In this paper we present a multi-lane detection method using omni-directional camera. The contribution of this paper is twofold. Firstly, we present an anisotropy steerable filter with the aim of get more reliable lane markings feature extraction under adverse(More)
Global localization is a challenging problem in which autonomous vehicle has to estimate the self-position with respect to a priori map using perception results. In this paper we present a vision-based localization method for autonomous Vehicles in urban environment. The localization process consists of two stages: coarse localization using topological map(More)
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