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Shape Similarity for 3D Video Sequences of People

Huang, P, Hilton, A and Starck, J (2010) Shape Similarity for 3D Video Sequences of People International Journal of Computer Vision, 89 (2-3). pp. 362-381.

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Abstract

This paper presents a performance evaluation of shape similarity metrics for 3D video sequences of people with unknown temporal correspondence. Performance of similarity measures is compared by evaluating Receiver Operator Characteristics for classification against ground-truth for a comprehensive database of synthetic 3D video sequences comprising animations of fourteen people performing twentyeight motions. Static shape similarity metrics shape distribution, spin image, shape histogram and spherical harmonics are evaluated using optimal parameter settings for each approach. Shape histograms with volume sampling are found to consistently give the best performance for different people and motions. Static shape similarity is extended over time to eliminate the temporal ambiguity. Time-filtering of the static shape similarity together with two novel shape-flow descriptors are evaluated against temporal ground-truth. This evaluation demonstrates that shape-flow with a multi-frame alignment of motion sequences achieves the best performance, is stable for different people and motions, and overcome the ambiguity in static shape similarity. Time-filtering of the static shape histogram similarity measure with a fixed window size achieves marginally lower performance for linear motions with the same computational cost as static shape descriptors. Performance of the temporal shape descriptors is validated for real 3D video sequence of nine actors performing a variety of movements. Time-filtered shape histograms are shown to reliably identify frames from 3D video sequences with similar shape and motion for people with loose clothing and complex motion.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
NameEmailORCID
Huang, PUNSPECIFIEDUNSPECIFIED
Hilton, AUNSPECIFIEDUNSPECIFIED
Starck, JUNSPECIFIEDUNSPECIFIED
Date : 1 September 2010
Identification Number : 10.1007/s11263-010-0319-9
Depositing User : Symplectic Elements
Date Deposited : 28 Mar 2017 15:00
Last Modified : 31 Oct 2017 14:19
URI: http://epubs.surrey.ac.uk/id/eprint/111045

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