Zernike velocity moments for sequence-based description of moving features

被引:38
作者
Shutler, J. D.
Nixon, M. S.
机构
[1] Plymouth Marine Lab, Remote Sensing Grp, Plymouth PL1 3DH, Devon, England
[2] Univ Southampton, Dept Elect & Comp Sci, Southampton SO17 1BJ, Hants, England
关键词
statistical moments; Zernike moments; motion; velocity moments; gait;
D O I
10.1016/j.imavis.2005.12.001
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The increasing interest in processing sequences of images motivates development of techniques for sequence-based object analysis and description. Accordingly, new velocity moments have been developed to allow a statistical description of both shape and associated motion through an image sequence. Through a generic framework motion information is determined using the established centralised moments, enabling statistical moments to be applied to motion based time series analysis. The translation invariant Cartesian velocity moments suffer from highly correlated descriptions due to their non-orthogonality. The new Zernike velocity moments overcome this by using orthogonal spatial descriptions through the proven orthogonal Zernike basis. Further, they are translation and scale invariant. To illustrate their benefits and application the Zernike velocity moments have been applied to gait recognition-an emergent biometric. Good recognition results have been achieved on multiple datasets using relatively few spatial and/or motion features and basic feature selection and classification techniques. The prime aim of this new technique is to allow the generation of statistical features which encode shape and motion information, with generic application capability. Applied performance analyses illustrate the properties of the Zernike velocity moments which exploit temporal correlation to improve a shape's description. It is demonstrated how the temporal correlation improves the performance of the descriptor under more generalised application scenarios, including reduced resolution imagery and occlusion. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:343 / 356
页数:14
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