Hybrid Lossless-Lossy Compression for Depth-Sensor Streams

Abstract

We developed and evaluated different schemes for the real-time compression of multiple depth image streams. Our analysis suggests that a hybrid lossless-lossy compression approach provides a good tradeoff between quality and compression ratio. Lossless compression based on run length encoding is used to preserve the information of the highest bits of the depth image pixels. The lowest 10-bits of a depth pixel value are directly encoded in the Y channel of a YUV image and encoded by a x264 codec. Our experiments show that the proposed method can encode and decode multiple depth image streams in less than 12 ms on average. Depending on the compression level, which can be adjusted during application runtime, we are able to achieve a compression ratio of about 4:1 to 20:1. Initial results indicate that the quality for 3D reconstructions is almost indistinguishable from the original for a compression ratio of up to 10:1.

Comparison of the resulting 3D reconstruction from 2 overlapping Kinect V2

Publication

Liu, Y., Beck, S., Wang, R., Li, J., Xu, H., Yao, S., Tong, X., Froehlich, B.
Hybrid Lossless-Lossy Compression for Real-Time Depth-Sensor Streams in 3D Telepresence Applications
In: Ho YS., Sang J., Ro Y., Kim J., Wu F. (eds) Advances in Multimedia Information Processing -- PCM 2015. Lecture Notes in Computer Science, vol 9314. Springer, Cham, pp. 442-452.
DOI=10.1007/978-3-319-24075-6_43
[preprint]