Semester

Spring

Date of Graduation

2024

Document Type

Problem/Project Report

Degree Type

MS

College

Davis College of Agriculture, Natural Resources and Design

Department

Division of Resource Economics & Management

Committee Chair

Paul Kinder

Committee Member

Jeremy Dawson

Committee Member

Walter Veselka

Abstract

Gait patterns are a class of biometric information pertaining to the way a person moves and poses. Gait information is unique to each person and can be used to identify and reidentify people. Historically, this task has been achieved through the use of multiple ground-based imaging sensors. However, as Unmanned Aerial Vehicles (UAVs) advance, they present the opportunity to evolve the process of persons identification and re-identification. Collecting human gait data using UAVs at distances ranging from 20m to 500m and altitudes ranging from 0m to 120m is a challenging task. The current biometric data collection methods, primarily designed for ground-level and close-range scenarios, need to be revised to address the complexities associated with UAV-based gait data collection. The challenges include the need for precision in capturing gait patterns from elevated angles, the impact of atmospheric conditions on data accuracy at altitude, and the limitations of traditional gait recognition technologies when applied in aerial settings. The absence of standardized protocols and optimized algorithms for UAV-based human gait data collection further increases the difficulty of achieving reliable human identification and re-identification outcomes. This problem report aims to highlight these challenges and guide future research efforts toward developing practical solutions for implementing UAVs in collecting human gait data at a distance and altitude.

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