Covariate conscious approach for Gait recognition based upon Zernike moment invariants

Gait recognition i.e. identification of an individual from his/her walking pattern is an emerging field. While existing gait recognition techniques perform satisfactorily in normal walking conditions, there performance tend to suffer drastically with variations in clothing and carrying conditions. In this work, we propose a novel covariate cognizant framework to deal with the presence of such covariates. We describe gait motion by forming a single 2D spatio-temporal template from video sequence, called Average Energy Silhouette image (AESI). Zernike moment invariants (ZMIs) are then computed to screen the parts of AESI infected with covariates. Following this, features are extracted from Spatial Distribution of Oriented Gradients (SDOGs) and novel Mean of Directional Pixels (MDPs) methods. The obtained features are fused together to form the final well-endowed feature set. Experimental evaluation of the proposed framework on three publicly available datasets i.e. CASIA dataset B, OU-ISIR Treadmill dataset B and USF Human-ID challenge dataset with recently published gait recognition approaches, prove its superior performance.Comment: 11 page

Estimativa de estatura em indivíduos vivos por meio de imagens no âmbito pericial criminal : estudo de caso simulado

Esse estudo objetiva realizar uma análise comparativa de dois métodos científicos utilizados, na perícia criminal, para estimativa da estatura de indivíduo por meio de imagens, visando apontar a técnica que mais se aproxima da estatura real conhecida, em ambiente fechado, frente a uma situação controlada, ou seja, livre de circulação de indivíduos. Para tanto, foi mensurada a estatura real do indivíduo, de 44 anos, sexo feminino. Foram capturadas imagens do indivíduo pela simulação de sistema de vigilância por vídeo. Os exames foram realizados através destas imagens, analisadas em microcomputadores, utilizando softwares livres, captadas por câmera fotográfica digital, em ambiente fechado e controlado, obtendo resultados por estatística descritiva. As imagens obtidas foram analisadas por três examinadores, treinados e calibrados, sem que houvesse conhecimento entre eles dos resultados e da estatura real do indivíduo analisado na amostra. Na Técnica Sobreposição de Gabarito, os três examinadores obtiveram o mesmo valor de mediana (163 cm), estimados no intervalo entre 162 cm e 165 cm. Para a Foto Adaptada, os valores foram estimados no intervalo entre 160 cm e 165 cm. Conclui-se que as duas técnicas propostas para estimativa de estatura em indivíduos vivos por meio de imagens, como complementar no processo de identificação humana, no âmbito pericial criminal, se mostraram confiáveis e válidas, não apresentando diferença estatística nas três observações de cada examinador. Importante considerar que as imagens da pesquisa apresentavam boa qualidade e mínima distorção, proporcionando adequada visualização do indivíduo em cena, o que de fato, nem sempre é realidade na rotina pericial.This study aims to carry out a comparative analysis of two scientific methods used, in criminal expertise, to estimate the height of an individual through images, aiming to point out the technique that most closely approximates the known real height, in a closed environment, in a controlled situation, that is, free movement of individuals. For that, the real height of the individual, 44 years old, female, was measured. Images of the individual were captured by simulating a video surveillance system. The exams were performed through these images, analyzed in microcomputers, using free software, captured by a digital camera, in a closed and controlled environment, obtaining results by descriptive statistics. The images obtained were analyzed by three trained and calibrated examiners, without any knowledge among them about the results and the actual height of the individual analyzed in the sample. In the Template Overlap Technique, the three examiners obtained the same median value (163 cm), estimated in the range between 162 cm and 165 cm. For the Adapted Photo, the values were estimated in the range between 160 cm and 165 cm. It is concluded that the two techniques proposed for estimating height in living individuals through images, as a complement in the process of human identification, in the criminal forensic scope, proved to be reliable and valid, with no statistical difference in the three observations of each examiner. It is important to consider that the research images had good quality and minimal distortion, providing adequate visualization of the individual on the scene, which in fact is not always a reality in the forensic routine

Precise video feedback through live annotation of football

The domain of sports analysis is a huge field in sports science. Several different computer systems are available for doing analysis, both expensive and less expensive. Some specialize in specific sports such as football or ice hockey, while others are sports agnostic. However, a common property of most of these systems is that they try to give in-depth and detailed analysis of the sport in question. This thesis proposes and describes a system that provides the user with the ability to annotate interesting happenings during a live sporting event, through a non-invasive mobile device interface. The device permits focus on important happenings by filtering out unnecessary detail. Our system provides corresponding video of the annotations on the same mobile device, thereby facilitating the process of giving video feedback to the involved coaches and players. We have implemented a prototype of the system that enables evaluation of this idea, and through case studies with Tromsø Idrettslag, a Norwegian Premier League football club, we show its usefulness and applicability

Human Gait Based Relative Foot Sensing for Personal Navigation

Human gait dynamics were studied to aid the design of a robust personal navigation and tracking system for First Responders traversing a variety of GPS-denied environments. IMU packages comprised of accelerometers, gyroscopes, and magnetometer are positioned on each ankle. Difficulties in eliminating drift over time make inertial systems inaccurate. A novel concept for measuring relative foot distance via a network of RF Phase Modulation sensors is introduced to augment the accuracy of inertial systems. The relative foot sensor should be capable of accurately measuring distances between each node, allowing for the geometric derivation of a drift-free heading and distance. A simulation to design and verify the algorithms was developed for five subjects in different gait modes using gait data from a VICON motion capture system as input. These algorithms were used to predict the distance traveled up to 75 feet, with resulting errors on the order of one percent

Gait analysis and recognition for automated visual surveillance

Human motion analysis has received a great attention from researchers in the last decade due to its potential use in different applications such as automated visual surveillance. This field of research focuses on the perception and recognition of human activities, including people identification. We explore a new approach for walking pedestrian detection in an unconstrained outdoor environment. The proposed algorithm is based on gait motion as the rhythm of the footprint pattern of walking people is considered the stable and characteristic feature for the classification of moving objects. The novelty of our approach is motivated by the latest research for people identification using gait. The experimental results confirmed the robustness of our method to discriminate between single walking subject, groups of people and vehicles with a successful detection rate of 100%. Furthermore, the results revealed the potential of our method to extend visual surveillance systems to recognize walking people. Furthermore, we propose a new approach to extract human joints (vertex positions) using a model-based method. The spatial templates describing the human gait motion are produced via gait analysis performed on data collected from manual labeling. The Elliptic Fourier Descriptors are used to represent the motion models in a parametric form. The heel strike data is exploited to reduce the dimensionality of the parametric models. People walk normal to the viewing plane, as major gait information is available in a sagittal view. The ankle, knee and hip joints are successfully extracted with high accuracy for indoor and outdoor data. In this way, we have established a baseline analysis which can be deployed in recognition, marker-less analysis and other areas. The experimental results confirmed the robustness of the model-based approach to recognise walking subjects with a correct classification rate of 95% using purely the dynamic features derived from the joint motion. Therefore, this confirms the early psychological theories claiming that the discriminative features for motion perception and people recognition are embedded in gait kinematics. Furthermore, to quantify the intrusive nature of gait recognition we explore the effects of the different covariate factors on the performance of gait recognition. The covariate factors include footwear, clothing, carrying conditions and walking speed. As far as the author can determine, this is the first major study of its kind in this field to analyse the covariate factors using a model-based method.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Measuring pedestrian gait using low resolution infrared people counters

This thesis describes research conducted into the measure- ment of pedestrian movement. It starts with an examination of current pedestrian detection and tracking systems, looking at several different technologies including image-processing systems. It highlights, as other authors have, that there is still a substantial gap between the abilities of existing pedestrian measurement and tracking systems and the requirements of users of such systems. After the review it provides an introduction to human gait and its use as a biometric. It then examines the IRISYS people counter, a low resolution infrared detector, used for this research. The detector's advantages and disadvantages are discussed, a detailed description of the data produced is provided. The thesis then describes in detail a study establishing that human gait information can be measured by the IRISYS people counter. It examines the use of the detectors in stereo to measure the height of the people; however the results are not impressive. During this investigation the presence of oscillations likely to relate to this walking gait is noted in the data. A second study is carried out confirming that the noted oscillation originates from human gait and further data is gathered to enable the development of measurement algorithms. The magnitude of the walking oscillation noted is examined in detail. It is found to be both individualistic and highly correlated to gender. A gender distribution algorithm is presented and evaluated on data captured in two different locations. These show very promising results. Several different methods are described for processing the infor-mation to extract a measure of cadence. The cadence is found to be individualistic and shows interesting correlations to height and leg length. This thesis advances the field of pedestrian measurement by conducting pedestrian motion studies and developing algorithms for measuring human gait.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Person Identification using Automatic Height and Stride Estimation

We present a parametric method to automatically identify people in monocular low-resolution video by estimating the height and stride parameters of their gait. Stride parameters (stride length and cadence) are functions of body height, weight, and gender. Previous work has demonstrated effective use of these biometrics for identification and verification of people. In this paper, we show that performance is significantly improved by using height as an additional discriminant feature. Height is estimated by segmenting the person from the background and fitting their apparent height to a time-dependent model. With a database of 45 people and 4 samples of each, we show that a person is correctly identified with 49 % probability when using both height and stride parameters, compared with 21 % when using stride parameters only. Height estimates for this configuration are accurate to within � � � � Ñ. This method works with low-resolution images of people, and is robust to changes in lighting, clothing, and tracking errors.

Measuring pedestrian gait using low resolution infrared people counters

This thesis describes research conducted into the measure- ment of pedestrian movement. It starts with an examination of current pedestrian detection and tracking systems, looking at several different technologies including image-processing systems. It highlights, as other authors have, that there is still a substantial gap between the abilities of existing pedestrian measurement and tracking systems and the requirements of users of such systems.After the review it provides an introduction to human gait and its use as a biometric. It then examines the IRISYS people counter, a low resolution infrared detector, used for this research. The detector's advantages and disadvantages are discussed, a detailed description of the data produced is provided. The thesis then describes in detail a study establishing that human gait information can be measured by the IRISYS people counter. It examines the use of the detectors in stereo to measure the height of the people; however the results are not impressive. During this investigation the presence of oscillations likely to relate to this walking gait is noted in the data.A second study is carried out confirming that the noted oscillation originates from human gait and further data is gathered to enable the development of measurement algorithms. The magnitude of the walking oscillation noted is examined in detail. It is found to be both individualistic and highly correlated to gender. A gender distribution algorithm is presented and evaluated on data captured in two different locations. These show very promising results. Several different methods are described for processing the infor-mation to extract a measure of cadence. The cadence is found to be individualistic and shows interesting correlations to height and leg length.This thesis advances the field of pedestrian measurement by conducting pedestrian motion studies and developing algorithms for measuring human gait