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Detection and classification of traffic signs is one of the most studied Advanced Driver Assistance Systems (ADAS) and some solutions are already installed in vehicles. Nevertheless these systems still have room for improvement in terms of speed and performance. When driving at high speed, warning systems require very fast processing of the video stream in order to lose as few frames as possible and...
In this paper, a robust background extraction and novel object detection are proposed, which comprise of filtering operations to detect non background objects in a monitoring scene. Conventionally, a statistical background model is extracted by using a training sequence without foreground objects and the background model parameters are being updated continuously to adapt changes in the scene. However,...
We study the problem of robust pedestrian detection. A new descriptor, Pyramidal Statistics of Oriented Filtering (PSOF), is proposed for shape representation. Unlike one-scale gradient-based methods, the PSOF descriptor constructs an image pyramid and uses a Gabor filter bank to obtain multi-scale pixel-level orientation information. Then, locally normalized pyramidal statistics of these Gabor responses...
The objective of this work is the detection of object classes. An improved method is used for object detection and segmentation in real-world multiple-object scenes. It has two stages. In the first stage this method develops a novel technique to extract class-discriminative boundary fragments, and then boosting is used to select discriminative boundary fragments (weak detectors) toform a strong "boundary-fragment-model"...
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