Location-driven Retrieval of Images Collected by a Mobile Robot

Mobile robot teleoperation is a method for a human user to interact with a mobile robot over time and distance. Successful teleoperation depends on how well sensor images taken by the mobile robot are visualized to the user. To enhance the efficiency and the flexibility of the visualization, an image retrieval system on such a robot's image database would be very useful. The main difference of this image retrieval problem from the standard one is that due to variety of viewing conditions, there exist various of relevant images. The main contribution of this paper is to propose an efficient retrieval approach for such a problem by utilizing correlation between visual features and real world locations of images. An active learning technique based on support vector machine is extended for this aim. The second contribution is to present a multi-hypothesis approach to deal with location uncertainty inherent in real world applications.