# A multimodal lossless coding method for skeletons in videos

## TL;DR

This paper introduces a multimodal lossless coding method for skeleton data in videos, combining spatial and temporal redundancy reduction techniques to improve compression efficiency significantly.

## Contribution

It presents the first multimodal skeleton coding tool with three schemes that adaptively switch for better compression of video skeleton data.

## Key findings

- Achieves 74.4% size reduction on surveillance sequences
- Achieves 54.7% size reduction on overall test sequences
- Demonstrates effective lossless skeleton data compression

## Abstract

Nowadays, skeleton information in videos plays an important role in human-centric video analysis but effective coding such massive skeleton information has never been addressed in previous work. In this paper, we make the first attempt to solve this problem by proposing a multimodal skeleton coding tool containing three different coding schemes, namely, spatial differential-coding scheme, motionvector-based differential-coding scheme and inter prediction scheme, thus utilizing both spatial and temporal redundancy to losslessly compress skeleton data. More importantly, these schemes are switched properly for different types of skeletons in video frames, hence achieving further improvement of compression rate. Experimental results show that our approach leads to 74.4% and 54.7% size reduction on our surveillance sequences and overall test sequences respectively, which demonstrates the effectiveness of our skeleton coding tool.