Real-Time Simultaneous Localisation and Mapping with a Single Camera
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM Computing Surveys (CSUR)
MonoSLAM: Real-Time Single Camera SLAM
IEEE Transactions on Pattern Analysis and Machine Intelligence
Combining monoSLAM with object recognition for scene augmentation using a wearable camera
Image and Vision Computing
Journal of Field Robotics - Visual Mapping and Navigation Outdoors
Inverse Depth Parametrization for Monocular SLAM
IEEE Transactions on Robotics
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The majority of visual SLAM techniques utilize interest points as landmarks. Therefore, they suffer from two main problems; scalability and data association reliability. Recently, there has been increasing interest in using higher level object description to reduce the number of tracked features and improve the data association among frames. In this paper, a simple visual mono SLAM algorithm is presented utilizing objects as landmarks and uses fast template matching to track predefined templates of these objects in an indoor environment. The results are described for real experiments with an indoor mobile robot platform. The performance of the proposed technique is evaluated and compared to recent methods.