A Study on Human recognition from the Body shapes when Face Identification Fails

Author:

Samantula Mohankrishna1,Gorla Srinivas1,D Lalitha Bhaskari2

Affiliation:

1. GITAM University

2. Andhra University

Abstract

Abstract Is it possible to identify a person where face recognition fails? This question has motivated us to search for the available procedures with which the task of human identification can be achieved. In this survey, various approaches that support the fact of identifying the person when the Face identification fails with the information on hand of person’s body structure and shapes. Here an attempt is made to consolidate and relates seemingly different terminology and methods which talks about the process involving how one does recognize a person when face identification fails? In general, when face identification fails, humans still tend to recognize the person based on the structure body posture and some time even from the back relying on the body but are unaware of doing so. Our objective is to develop a basic, straightforward system of person recognition based on person’s body type and gait movement. This primary recognition technique offers a lower constraint for assessing more complex procedures.

Publisher

Research Square Platform LLC

Reference37 articles.

1. Rice et al (2013) ” Unaware Person Recognition from the Body When Face Identification Fails”, Psychological Science, Vol. 24, No. 11 pp. 2235–2243

2. The contribution of the body and motion to whole person recognition;Noa Simhi G;Vision Res,2016

3. “Body Inversion Effects with Photographic Images of Body Postures: Is It about Faces?”;Axelsson;Front Psychol November,2019

4. Afzal, Godil (2003) Patrick Grother and Sandy Ressler “Human identification from body shape”, Fourth International Conference on 3-D Digital Imaging and Modeling, 3DIM 2003. Proceedings. IEEE

5. Robert T, Collins R, Gross, Shi J ” Silhouette-based Human Identification from Body Shape and Gait”, Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition 0-7695-1602-5/02

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