scholarly journals Kinematic cues for person identification from biological motion

2007 ◽  
Vol 69 (2) ◽  
pp. 241-253 ◽  
Author(s):  
Cord Westhoff ◽  
Nikolaus F. Troje
Keyword(s):  
Biological Motion ◽  
Person Identification

scholarly journals Person identification from biological motion: Effects of structural and kinematic cues

2005 ◽  
Vol 67 (4) ◽  
pp. 667-675 ◽  
Author(s):  
Nikolaus F. Troje ◽  
Cord Westhoff ◽  
Mikhail Lavrov
Keyword(s):  
Biological Motion ◽  
Person Identification

scholarly journals Person identification across actions from biological motion

2010 ◽  
Vol 8 (6) ◽  
pp. 912-912
Author(s):  
G. Holland ◽  
S. Mody ◽  
N. Troje
Keyword(s):  
Biological Motion ◽  
Person Identification

The Influence of (Biological) Form on the Perception of Biological Motion

2014 ◽  
Author(s):  
Luke Miller ◽  
Burcu A. Urgen ◽  
Maria Florendo ◽  
Jennifer Cook ◽  
Ayse P. Saygin
Keyword(s):  
Biological Motion ◽  
Biological Form ◽  
Perception Of Biological Motion

Emotional states affect the retention of biological motion in working memory.

Emotion ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 1446-1461 ◽  
Author(s):  
Yang Guo ◽  
Wenmin Li ◽  
Xiqian Lu ◽  
Xiaodong Xu ◽  
Fangfang Qiu ◽  
...  
Keyword(s):  
Working Memory ◽  
Biological Motion ◽  
Emotional States

Human Ear Pattern Recognition System

2017 ◽  
Vol 7 (8) ◽  
pp. 117 ◽  
Author(s):  
V. Jagan Naveen ◽  
K. Krishna Kishore ◽  
P. Rajesh Kumar
Keyword(s):  
Pattern Recognition ◽  
Expectation Maximization Algorithm ◽  
Recognition System ◽  
Modern World ◽  
Person Identification ◽  
Biometric Systems ◽  
Different Types ◽  
Recognition Systems ◽  
Human Ear ◽  
Pca Algorithm

In the modern world, human recognition systems play an important role to   improve security by reducing chances of evasion. Human ear is used for person identification .In the Empirical study on research on human ear, 10000 images are taken to find the uniqueness of the ear. Ear based system is one of the few biometric systems which can provides stable characteristics over the age. In this paper, ear images are taken from mathematical analysis of images (AMI) ear data base and the analysis is done on ear pattern recognition based on the Expectation maximization algorithm and k means algorithm.  Pattern of ears affected with different types of noises are recognized based on Principle component analysis (PCA) algorithm.

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