3D Reconstruction and Object Detection for HoloLens
Zequn Wu, Tianhao Zhao, Chuong Nguyen
Abstract
Current smart glasses such as HoloLens excel at positioning within the physical environment, however object and task recognition are still relatively primitive. We aim to expand the available benefits of MR/AR systems by using semantic object recognition and 3D reconstruction. Particularly in this preliminary study, we successfully use a HoloLens to build 3D maps, recognise and count objects in a working environment. This is achieved by offloading these computationally expensive tasks to a remote GPU server. To further achieve realtime feedback and parallelise tasks, object detection is performed on 2D images and mapped to 3D reconstructed space. Fusion of multiple views of 2D detection is additionally performed to refine 3D object bounding boxes and separate nearby objects.