Multiple description scalar quantization based 3D mesh coding

Date

2006-10-11

Author

Bici, M. Oguz
Akar, Gözde

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

169
views

0
downloads

In this paper, we address the problem of 3D Model transmission over error-prone channels using multiple description coding (MDC). The objective of MDC is to encode a source into multiple bitstreams, called descriptions, supporting multiple quality levels of decoding. Compared to layered coding techniques, each description can be decoded independently to approximate the model. In the proposed approach, the mesh geometry is compressed using multiresolution geometry compression. Then multiple descriptions are obtained by applying Multiple Description Scalar Quantization (MDSQ) to the obtained wavelet coefficients. Experimental results show that, the proposed approach achieves competitive compression performance compared with existing multiple description methods.

Subject Keywords

Decoding, Encoding, Quantization, Multipath channels, Computer graphics, Multimedia communication

URI

https://hdl.handle.net/11511/36889

DOI

https://doi.org/10.1109/icip.2006.312485

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Multiple description coding of animated meshes Bici, M. Oguz; Akar, Gözde (Elsevier BV, 2010-11-01) In this paper, we propose three novel multiple description coding (MDC) methods for reliable transmission of compressed animated meshes represented by series of 3D static meshes with same connectivity. The proposed methods trade off reconstruction quality for error resilience to provide the best expected reconstruction of 3D mesh sequence at the decoder side. The methods are based on layer duplication and partitioning of the set of vertices of a scalable coded animated mesh by either spatial or temporal sub...
Multiple Description Coding of 3D Dynamic Meshes Based on Temporal Subsampling Bici, M. Oguz; Akar, Gözde (2010-01-21) In this paper, we propose a Multiple Description Coding (MDC) method for reliable transmission of compressed time consistent 3D dynamic meshes. It trades off reconstruction quality for error resilience to provide the best expected reconstruction of 3D mesh sequence at the decoder side. The method is based on partitioning the mesh frames into two sets by temporal subsampling and encoding each set independently by a 3D dynamic mesh coder. The encoded independent bitstreams or so-called descriptions are transm...
Multiple description coding of 3D geometry with forward error correction codes Bici, M. Oguz; Norkin, Andrey; Akar, Gözde; Gotchev, Atanas; Astola, Jaakko (2007-05-09) This work presents a multiple description coding (MDC) scheme for compressed three dimensional (3D) meshes based on forward error correction (FEC). It allows flexible allocation of coding redundancy for reliable transmission over error-prone channels. The proposed scheme is based on progressive geometry compression, which is performed by using wavelet transform and modified SPIHT algorithm. The proposed algorithm is optimized for varying packet loss rates (PLR) and channel bandwidth. Modeling distortion-rat...
Multiple Model Adaptive Estimation Algorithm for Systems with Parameter Change Söken, Halil Ersin (2016-01-01) This paper presents an autonomous multiple model (AMM) estimation algorithm for systems with sudden parameter changes. Estimates of a bank of Kalman filters (KFs) are merged based on a newly defined likelihood function. The function is composed of two measures, one for weighting the filters during the steady state mode and the other for weighting when there is a change in the parameters. Compared to the interacting multiple model (IMM) method, the KFs do not interact but compete on the basis of the likeliho...
Deep learning-based encoder for one-bit quantization Balevi, Eren; Andrews, Jeffrey G. (2019-12-01) © 2019 IEEE.This paper proposes a deep learning-based error correction coding for AWGN channels under the constraint of one-bit quantization in receivers. An autoencoder is designed and integrated with a turbo code that acts as an implicit regularization. This implicit regularizer facilitates approaching the Shannon bound for the one-bit quantized AWGN channels even if the autoencoder is trained suboptimally, since one-bit quantization stymies ideal training. Our empirical results show that the proposed cod...

Citation Formats

M. O. Bici and G. Akar, “Multiple description scalar quantization based 3D mesh coding,” 2006, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/36889.