Abstract. In the paper a method for fast IMU calibration is described. The method need previously calibrated IMU, called standard IMU. Standard IMU and IMU to be calibrated have to have a solid mechanical connection. Then a sequention of movement is done and an outputs from both IMUs are recorded simultaneously. Outputs can be recorded with different sampling frequency for each IMU. Then an iterative procedure is employed for simultaneous fitting signal from calibrated IMU to standard IMU and aligning both signals, using least squares method. The point in 2-parameter space, that give best fit allows to calculate a calibration matrixes that describes linear dependence beetwen calibrated and sandard sensors. A method allows to calibrate all three-axis sensors (accelerometers, angular rate sensors and magnetometers) at the same time. Method is not-time-consuming and can be used to convenient in-field and on-object calibration of IMUs without a complicated calibration setup.

This paper presents a method for human detection using a laser scanner with vision or infrared images. Mobile applications require reliable and efficient methods for human detection, especially as a part of driver assistance systems, including pedestrian collision systems. The authors propose an efficient method for multimodal human detection based on a combination of the features and context information. Strictly, the human is detected in the vision/infrared images using a combination of local binary patterns and histogram of oriented gradients features with a neural network in a cascade manner. Next, using coordinates of detected humans from the vision system, the moving trajectory is predicted until the scanner working distance is reached by the individual human. Then the segmentation of data from the laser scanner is further carried out with respect to the predicted trajectory. Finally, human detection in the laser scanner working distance is performed based on modelling of the human legs. The modelling is based on the adaptive breakpoint detection algorithm and proposed improved polylines definition and fitting algorithm. The authors conducted a set of experiments in predefined scenarios, discussed the identified weakness and advantages of the proposed method, and outlined detailed future work, especially for night-time and low-light conditions.

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