Fig. 1. Spatiotemporal division multiplexing approach for suppressing the deterioration of a 3D holographic video reconstructed from a point-cloud model comprising a huge number of object points.

Fig. 2. Spatiotemporal division multiplexing approach using moving image features.

Fig. 3. Reconstructed 3D image from a 3D object “fountain” comprising 1,064,462 object points.

Fig. 4. Multi-GPU cluster system with multiple GPUs connected by a gigabit Ethernet network and a single SLM.

Fig. 5. Pipeline processing for the spatiotemporal electroholography system shown in Fig. 2.

Fig. 6. Read data processing and CGH calculation on each CGH calculation node in the multi-GPU cluster system shown in Fig. 4. (a) Serial computing. (b) Parallel computing.

Fig. 7. Comparison of the total display time for every 12 frames using serial computing shown in Fig. 6(a) with that using parallel computing shown in Fig. 6(b) when the number of object points is 1,200,000.

Fig. 8. Display-time interval T shown in Fig. 5 plotted versus the number of object points when using the spatiotemporal division multiplexing approach using moving image features implemented on the multi-GPU cluster system shown in Fig. 4.

Fig. 9. Snapshot of a reconstructed 3D video (Video 1).