Gait Evaluation Using Procrustes and Euclidean Distance Matrix Analysis
نویسندگان
چکیده
منابع مشابه
Gait Recognition Using Procrustes Shape Analysis and Shape Context
This paper proposes a novel algorithm for individual recognition by gait. The method of Procrustes shape analysis is used to produce Procrustes Mean Shape (PMS) as a compressed representation of gait sequence. PMS is adopted as the gait signature in this paper. Instead of using the Procrustes mean shape distance as a similarity measure, we introduce shape context descriptor to measure the simil...
متن کاملGait recognition based on Procrustes shape analysis
Gait recognition has recently attracted increasing attention, especially in vision-based human identification at a distance in visual surveillance. This paper proposes a simple but efficient gait recognition algorithm based on statistical shape analysis. For each gait sequence, a background subtraction procedure is used to segment spatial silhouettes of the walking figures from the background. ...
متن کاملEuclidean distance matrix completion problems
A Euclidean distance matrix is one in which the (i, j) entry specifies the squared distance between particle i and particle j. Given a partially-specified symmetric matrix A with zero diagonal, the Euclidean distance matrix completion problem (EDMCP) is to determine the unspecified entries to make A a Euclidean distance matrix. We survey three different approaches to solving the EDMCP.We advoca...
متن کاملEuclidean distance matrix analysis: a coordinate-free approach for comparing biological shapes using landmark data.
For problems of classification and comparison in biological research, the primary focus is on the similarity of forms. A biological form can be conveniently defined as consisting of size and shape. Several approaches for comparing biological shapes using landmark data are available. Lele (1991a) critically discusses these approaches and proposes a new method based on the Euclidean distance matr...
متن کاملA simple method for visualization of influential landmarks when using euclidean distance matrix analysis.
Euclidean distance matrix analysis (EDMA) differs from most other morphometric methods for the analysis of landmark coordinate data in that it is coordinate-system invariant. However, strict adherence to coordinate-system invariance (for both biological and statistical reasons) introduces some difficulty in using graphic aids for the analysis and interpretation of EDMA results. We present a sim...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Journal of Biomedical and Health Informatics
سال: 2019
ISSN: 2168-2194,2168-2208
DOI: 10.1109/jbhi.2018.2875812