Paulo Vinicius Koerich Borges

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— Automated fire detection is an active research topic in computer vision. In this paper we propose and analyze a new method for identifying fire in videos. Computer vision based fire detection algorithms are usually applied in CCTV surveillance scenarios with controlled background. In contrast, the proposed method can be applied not only to surveillance(More)
Reliable motion estimation is a key component for autonomous vehicles. We present a visual odometry method for ground vehicles using template matching. The method uses a downward facing camera perpendicular to the ground and estimates the motion of the vehicle by analyzing the image shift from frame to frame. Specifically, an image region (template) is(More)
—Understanding human behaviors is a challenging problem in computer vision that has recently seen important advances. Human behavior understanding combines image and signal processing, feature extraction, machine learning and 3D geometry. Application scenarios range from surveillance to indexing and retrieval, from patient care to industrial safety and(More)
In this paper we propose a new image event detection method for identifying fire in videos. Traditional image based fire detection is often applied in surveillance camera scenarios with well behaved background. In contrast, the proposed method is applied for retrieval of fire catastrophes in newscast content, such that there is great variation in fire and(More)
—Reliable lane detection is a key component of autonomous vehicles supporting navigation in urban environments. This paper introduces the GOLDIE(Geometric Overture for Lane Detection by Intersections Entirety) system, a vision-based software architecture that uses an on-board single camera to determine the position of road lanes with respect to the vehicle.(More)