J. Tran, A. Ufkes, A. Ferworn, M. Fiala
A 3D map of the interior of a disaster site that pinpoints the location of trapped victims would greatly aid search and rescue efforts. We propose using a canine-mounted RGB-D sensor, a trained rescue dog can carry an image sensor through the site to build a 3D model useful for rescuers. However, the registration of the data provides challenges beyond those typically faced in scene reconstruction due to the rapid motion and sudden pose changes. We provide a solution whereby a pre-processing step identifies good frames to combine from a stream of RGB-D image frames. These selected images are then combined into the larger model by calculating a relative pose using the 3D location of key points matched in the visible images. Results are presented of 3D models constructed using data collected from the canine platform.
Citation: J. Tran, A. Ufkes, A. Ferworn, M. Fiala, “3D Disaster Scene Reconstruction Using a Canine-Mounted RGB-D Sensor,” in Computer and Robot Vision (CRV), 2013 International Conference on, May 28 – 31 2013, Regina, SK, Canada, 2013