The aim of the presented work was the development of a tracking algorithm for a stereoscopic camera setup equipped with an additional inertial sensor. The input of the algorithm consists of the image sequence, angular velocity and linear acceleration vectors measured by the inertial sensor. The main assumption of the project was fusion of data streams from both sources to obtain more accurate ego-motion estimation. An electronic module for recording the inertial sensor data was built. Inertial measurements allowed a coarse estimation of the image motion field that has reduced its search range by standard image-based methods. Continuous tracking of the camera motion has been achieved (including moments of image information loss). Results of the presented study are being implemented in a currently developed obstacle avoidance system for visually impaired pedestrians.
The article describes a technique developed for identification of extrinsic parameters of a stereovision camera system for the purpose of image rectification without the use of reference calibration objects. The goal of the presented algorithm is the determination of the mutual position of cameras, under the assumption that they can be modeled by pinhole cameras, are separated by a fixed distance and are moving through a stationary scene. The developed method was verified experimentally on image sequences of a scene with a known structure.
The sensor-shifted stereo camera provides the mechanism for obtaining 3D information in a wide field of view. This novel kind of stereo requires a simpler matching process in comparison to convergence stereo. In addition to this, the uncertainty of depth estimation of a target point in 3D space is defined by the spatial quantization caused by the digital images. The dithering approach is a way to reduce the depth reconstruction uncertainty through a controlled adjustment of the stereo parameters that shift the spatial quantization levels. In this paper, a mathematical model that relates the stereo setup parameters to the iso-disparities is developed and used for depth estimation. The enhancement of the depth measurement accuracy for this kind of stereo through applying the dithering method is verified by simulation and physical experiment. For the verification, the uncertainty of the depth measurement using dithering is compared with the uncertainty produced by the direct triangulation method. A 49% improvement of the uncertainly in the depth reconstruction is proved.