Encoding Parameter Estimation for RDTC Optimized Compression and Streaming of Image-Based Scene Representations

TL;DR: This work presents a practical framework for parameter estimation for RDTC optimal encoding of image-based scene representations and shows that if a limited channel bitrate and computational power of client devices are taken into account, encoding can be performed in a RD optimal manner.

Abstract: Remote navigation in image-based scene representations requires random access to parts of the compressed reference image data to compose virtual views. The degree of dependencies introduced during compression has an impact on the effort that is required to access reference image data and at the same time delimits the rate-distortion (RD) tradeoff that can be achieved. If a limited channel bitrate and computational power of client devices are taken into account, encoding can be performed in a RD optimal manner with respect to the expected maximum transmission data rate (T) and decoding complexity (C). In this work we present a practical framework for parameter estimation for RDTC optimal encoding of image-based scene representations.