Identification of gait parameters from silhouette images

Gait analysis has applications not only in medical, rehabilitation and sports, but it can also play a decisive role in security and surveillance as a behavioral biometric factor. This paper discusses gait parameters extraction technique without using makers or sensors. Videos from a home digital camera are analyzed and a silhouette image based technique is used to identify gait parameter such as step length, stride length, silhouette height and width, foot length, center of gravity (COG) and gait signature. 10 healthy subject's sagittal view is considered in this research at RAMAN lab, MNIT Jaipur. Non-requirement of markers makes the system non-invasive, cheap, and also easier to implement. To ascertain the quality of data obtained, the data has been compared with the data extracted by marker based approaches for the same subject and satisfactory results conform that the proposed system is feasible and can be used in the aforementioned areas. This paper can help researchers by providing them with a general insight of the gait parameters extraction technique for gait analysis.

[1]  W. Eric L. Grimson,et al.  Gait analysis for recognition and classification , 2002, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition.

[2]  J. Little,et al.  Recognizing People by Their Gait: The Shape of Motion , 1998 .

[3]  W. T. Dempster,et al.  Properties of body segments based on size and weight , 1967 .

[4]  Hu Ng,et al.  Classification of human gait features with different apparel and walking speed , 2010, 10th International Conference on Information Science, Signal Processing and their Applications (ISSPA 2010).

[5]  Emanuele Trucco,et al.  Computer and Robot Vision , 1995 .

[6]  Hiroshi Murase,et al.  Moving object recognition in eigenspace representation: gait analysis and lip reading , 1996, Pattern Recognit. Lett..

[7]  Linda G. Shapiro,et al.  Computer and Robot Vision , 1991 .

[8]  Mark S. Nixon,et al.  Model-driven statistical analysis of human gait motion , 2002, Proceedings. International Conference on Image Processing.

[9]  Hu Ng,et al.  Extraction of human gait features from enhanced human silhouette images , 2009, 2009 IEEE International Conference on Signal and Image Processing Applications.

[10]  Seon-Woo Lee,et al.  Detection of Spatio-Temporal Gait Parameters by Using Wearable Motion Sensors , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[11]  Tieniu Tan,et al.  Automatic gait recognition based on statistical shape analysis , 2003, IEEE Trans. Image Process..

[12]  Madasu Hanmandlu,et al.  Silhouette based gait recognition based on the area features using both model free and model based approaches , 2013, 2013 IEEE International Conference on Technologies for Homeland Security (HST).

[13]  Andi Isra Mahyuddin,et al.  Gait Parameters Determination by 2D Optical Motion Analyzer System , 2011 .

[14]  Alfred D. Grant Gait Analysis: Normal and Pathological Function , 2010 .

[15]  W. Eric L. Grimson,et al.  Adaptive background mixture models for real-time tracking , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[16]  Yi Ma,et al.  Robust principal component analysis? , 2009, JACM.

[17]  Vijay Laxmi,et al.  Passive Marker Based Optical System for Gait Kinematics for Lower Extremity , 2015 .

[18]  Thierry Bouwmans,et al.  Background Subtraction for Visual Surveillance , 2012, Handbook of Soft Computing for Video Surveillance.

[19]  Namita Mittal,et al.  Identification of spatio-temporal and kinematics parameters for 2-D optical gait analysis system using passive markers , 2015, 2015 International Conference on Advances in Computer Engineering and Applications.

[20]  Mark S. Nixon,et al.  Developing a non-intrusive biometric environment , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[21]  M. O'Malley,et al.  Kinematic analysis of human walking gait using digital image processing , 1993, Medical and Biological Engineering and Computing.

[22]  D. Hatzinakos,et al.  Gait analysis and recognition using angular transforms , 2004, Canadian Conference on Electrical and Computer Engineering 2004 (IEEE Cat. No.04CH37513).

[23]  Shaou-Gang Miaou,et al.  A vision-based walking posture analysis system without markers , 2010, 2010 2nd International Conference on Signal Processing Systems.

[24]  Bir Bhanu,et al.  Individual recognition using gait energy image , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.