A vehicle detection system based on Haar and Triangle features

In recent years, the Viola and Jones rapid object detection approach became very popular. One aspect why this approach achieved acceptance is the numerical efficient computation of the Haar-like features on basis of the integral image. This efficiency is essential for sliding window techniques, where features have to be extracted for huge amounts of data. The main contribution of this paper is an efficient method to compute Triangle filters for feature extraction based on four integral images. The 2D Triangle filters are derived from 1D Bartlett functions. A comparison of Haar-like filters and the new Triangle filters is given by means of empirical results. The receiver operator characteristics reveal the superiority of the Triangle filters. Furthermore a vehicle detection system is described where the Triangle features are integrated. The system is based on a cascade of boosted classifiers, Haar and Triangle features, an adaptive sliding window and finally a Kalman filter.

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