Visualization1 Movie.avi

Hologram frames selected from video of paramecium and its reconstruction. Full video as seen through the augmented reality device

Visualization 1 Final.mp4

Visualization 1 shows a sample video of the experimental results comparing 2D tracking and 3D tracking using the proposed approach. In this video, a green-colored box represents a valid detection using YOLOv2 deep neural network (detection score more than 0.5) and a red-colored box represents the 2D bounding box of the object corresponding to a failed detection. As we can see, 2D imaging fails sporadically in tracking the object in degraded environments. In comparison, 3D integral imaging-based tracking performs much better in similar circumstances

Visualization.avi

Red blood cell fluctuation

Media 2: Improved resolution 3D object sensing and recognition using time multiplexed computational integral imaging

Originally published in Optics Express on 29 December 2003 (oe-11-26-3528

Media 2: Tracking biological microorganisms in sequence of 3D holographic microscopy images

Originally published in Optics Express on 20 August 2007 (oe-15-17-10761

Media 1: Improved resolution 3D object sensing and recognition using time multiplexed computational integral imaging

Originally published in Optics Express on 29 December 2003 (oe-11-26-3528

Media 2: Three-dimensional distortion-tolerant object recognition using integral imaging

Originally published in Optics Express on 15 November 2004 (oe-12-23-5795

Media 4: Improved resolution 3D object sensing and recognition using time multiplexed computational integral imaging

Originally published in Optics Express on 29 December 2003 (oe-11-26-3528

Media 3: Three-dimensional distortion-tolerant object recognition using integral imaging

Originally published in Optics Express on 15 November 2004 (oe-12-23-5795

Media 2: Distortion-tolerant 3D recognition of occluded objects using computational integral imaging

Originally published in Optics Express on 11 December 2006 (oe-14-25-12085