Obstacle detection quality as a problem-oriented approach to stereo vision algorithms estimation in road situation analysis
Journal of Physics: Conference Series, 2018•iopscience.iop.org
In this work we present a method for performance evaluation of stereo vision based obstacle
detection techniques that takes into account the specifics of road situation analysis to
minimize the effort required to prepare a test dataset. This approach has been designed to
be implemented in systems such as self-driving cars or driver assistance and can also be
used as problem-oriented quality criterion for evaluation of stereo vision algorithms.
detection techniques that takes into account the specifics of road situation analysis to
minimize the effort required to prepare a test dataset. This approach has been designed to
be implemented in systems such as self-driving cars or driver assistance and can also be
used as problem-oriented quality criterion for evaluation of stereo vision algorithms.
Abstract
In this work we present a method for performance evaluation of stereo vision based obstacle detection techniques that takes into account the specifics of road situation analysis to minimize the effort required to prepare a test dataset. This approach has been designed to be implemented in systems such as self-driving cars or driver assistance and can also be used as problem-oriented quality criterion for evaluation of stereo vision algorithms.
iopscience.iop.org
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