On-road vehicle detection based on effective hypothesis generation

This paper proposes an effective hypothesis generation for detection multi-vehicle using a monocular camera fixed on the host vehicle. In hypothesis generation (HG) step, we use linear model between the distance and vehicle size by using recursive least square. It generates effective image patches and improves the detection performance. In addition, it also reduces the computation time compared with sliding-window approach. In hypothesis verification (HV) step, we use the Histogram of Oriented Gradient (HOG) feature and Support Vector Machine (SVM). In our experiment, Caltech and IR datasets are used. The experimental result shows the improvement of running time and detection performance.