Gaussian Process Person Identifier Based on Simple Floor Sensors
EuroSSC '08 Proceedings of the 3rd European Conference on Smart Sensing and Context
People Identification Using Gait Via Floor Pressure Sensing and Analysis
EuroSSC '08 Proceedings of the 3rd European Conference on Smart Sensing and Context
Human identification by gait analysis
Proceedings of the 2nd International Workshop on Systems and Networking Support for Health Care and Assisted Living Environments
Gait recognition using wearable motion recording sensors
EURASIP Journal on Advances in Signal Processing - Special issue on recent advances in biometric systems: a signal processing perspective
Using ground reaction forces from gait analysis: body mass as a weak biometric
PERVASIVE'07 Proceedings of the 5th international conference on Pervasive computing
The design of a pressure sensing floor for movement-based human computer interaction
EuroSSC'07 Proceedings of the 2nd European conference on Smart sensing and context
Efficient human action and gait analysis using multiresolution motion energy histogram
EURASIP Journal on Advances in Signal Processing - Special issue on video analysis for human behavior understanding
Results of using a wireless inertial measurirlg system to quantify gait motions in control subjects
IEEE Transactions on Information Technology in Biomedicine
Analysis of time domain information for footstep recognition
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
Proceedings of the 13th international conference on Ubiquitous computing
An Analysis of Different Approaches to Gait Recognition Using Cell Phone Based Accelerometers
Proceedings of International Conference on Advances in Mobile Computing & Multimedia
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This paper describes the development of a prototype floor sensor as a gait recognition system. This could eventually find deployment as a standalone system (eg. a burglar alarm system) or as part of a multimodal biometric system. The new sensor consists of 1536 individual sensors arranged in a 3m by 0.5m rectangular strip with an individual sensor area of 3 cm2. The sensor floor operates at a sample rate of 22 Hz. The sensor itself uses a simple design inspired by computer keyboards and is made from low cost, off the shelf materials. Application of the sensor floor to a small database of 15 individuals was performed. Three features were extracted : stride length, stride cadence, and time on toe to time on heel ratio. Two of these measures have been used in video based gait recognition while the third is new to this analysis. These features proved sufficientto achieve an 80% recognition rate.