Month: October 2015
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Displacement priors
What is the target of all this ? Driving in an automotive scenario with a given speed and turnrate at any moment, we want to predict the displacement of a 2D-projection (pixel) between two frames: By using the camera-calibration, I can create artificial curves and walls as 3D point-sets and project them back to 2D.…
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Symmetry detection
This will probably become one of our modalities in the future: symmetry ! Thanks to the guys at hs-niederrhein, there is symmetry-detection-code that can already be used for some first estimates: This software implements the gradient product transform for symmetry detection that is described in the paper C. Dalitz, R. Pohle-Froehlich, F. Schmitt, M. Jeltsch:…
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Lane detection
Today I will try to detect some lanes.. Assumptions: – We know the lane-width (plus minus) – We are inside the middle of a lane – We know the camera geometry – Based on the turnrate of the IMU we can estimate the curvature of the street – A line in pixels can be detected…
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Training Cascades to detect cars
I spent some time on training several cascades to detect cars in ego-view automotive videos, and will now document what I’ve learned. I will use the existing OpenCV-tools. Data preparation ./cascadetraining/ -> pos/ 1000 images containing the desired object -> pos.info (containing the filenames of the objects, number of objects in the frame and bounding…