Gait Dynamics for Recognition and Classification

This paper describes a representation of the dynamics of human walking action for the purpose of person identification and classification by gait appearance. Our gait representation is based on simple features such as moments extracted from video silhouettes of human walking motion. We claim that our gait dynamics representation is rich enough for the task of recognition and classification. The use of our feature representation is demonstrated in the task of person recognition from video sequences of orthogonal views of people walking. We demonstrate the accuracy of recognition on gait video sequences collected over different days and times, and under varying lighting environments. In addition, preliminary results are shown on gender classification using our gait dynamics features

Detection and Estimation of an Optical Image by Photon-Counting Techniques

Statistical description of a photoelectric detector is given. The photosensitive surface of the detector is divided into many small areas, and the moment generating function of the photo-counting statistic is derived for large time-bandwidth product. The detection of a specified optical image in the presence of the background light by using the hypothesis test is discussed. The ideal detector based on the likelihood ratio from a set of numbers of photoelectrons ejected from many small areas of the photosensitive surface is studied and compared with the threshold detector and a simple detector which is based on the likelihood ratio by counting the total number of photoelectrons from a finite area of the surface. The intensity of the image is assumed to be Gaussian distributed spatially against the uniformly distributed background light. The numerical approximation by the method of steepest descent is used, and the calculations of the reliabilities for the detectors are carried out by a digital computer

Development of a Model to Predict the Likelihood of Complaints due to Assorted Tone-in-Noise Combinations

This paper develops a model to predict if listeners would be likely to complain due to annoyance when exposed to a certain noise signal with a prominent tone, such as those commonly produced by heating, ventilation, and air-conditioning systems. Twenty participants completed digit span tasks while exposed in a controlled lab to noise signals with differing levels of tones, ranging from 125 to 1000 Hz, and overall loudness. After completing the digit span tasks under each noise signal, from which task accuracy and speed of completion were captured, subjects were asked to rate level of annoyance and indicate the likelihood of complaining about the noise. Results show that greater tonality in noise has statistically significant effects on task performance by increasing the time it takes for participants to complete the digit span task; no statistically significant effects were found on task accuracy. A logistic regression model was developed to relate the subjective annoyance responses to two noise metrics, the stationary Loudness and Tonal Audibility, selected for the model due to high correlations with annoyance responses. The percentage of complaints model showed better performance and reliability over the percentage of highly annoyed or annoyed

Monitoring Activities from Multiple Video Streams: Establishing a Common Coordinate Frame

Passive monitoring of large sites typically requires coordination between multiple cameras, which in turn requires methods for automatically relating events between distributed cameras. This paper tackles the problem of self-calibration of multiple cameras which are very far apart, using feature correspondences to determine the camera geometry. The key problem is finding such correspondences. Since the camera geometry and photometric characteristics vary considerably between images, one cannot use brightness and/or proximity constraints. Instead we apply planar geometric constraints to moving objects in the scene in order to align the scene"s ground plane across multiple views. We do not assume synchronized cameras, and we show that enforcing geometric constraints enables us to align the tracking data in time. Once we have recovered the homography which aligns the planar structure in the scene, we can compute from the homography matrix the 3D position of the plane and the relative camera positions. This in turn enables us to recover a homography matrix which maps the images to an overhead view. We demonstrate this technique in two settings: a controlled lab setting where we test the effects of errors in internal camera calibration, and an uncontrolled, outdoor setting in which the full procedure is applied to external camera calibration and ground plane recovery. In spite of noise in the internal camera parameters and image data, the system successfully recovers both planar structure and relative camera positions in both settings

Pigmented basal cell carcinoma of the eyelid in Hispanics

Lily Koo Lin1, Han Lee2, Eli Chang11Department of Oculoplastics, Doheny Eye Institute, Los Angeles, CA, USA; 2Department of Dermatology, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USABackground: Pigmented basal cell carcinoma (PBCC) of the eyelid has not been well cited in the literature, and is often overlooked in the differential diagnosis of pigmented eyelid lesions. We aim to describe PBCC of the eyelid in Hispanic patients.Methods: Retrospective review of patients with eyelid skin cancer who presented to the Department of Dermatology at the Keck School of Medicine of the University of Southern California and the Doheny Eye Institute from January 2002 to November 2005.Results: Sixty-nine of the 79 patients with eyelid skin cancer had basal cell carcinoma. Eight of these patients were Hispanic. Four of the eight Hispanic patients had PBCC.Conclusions: Although eyelid PBCC is regarded as a rare condition, it may occur more commonly in the Hispanic population and should be remembered in the differential diagnosis of pigmented eyelid lesions.Keywords: pigmented basal cell carcinoma, eyelid, skin cancer, lesion

Gait Analysis for Classification

This thesis describes a representation of gait appearance for the purpose of person identification and classification. This gait representation is based on simple localized image features such as moments extracted from orthogonal view video silhouettes of human walking motion. A suite of time-integration methods, spanning a range of coarseness of time aggregation and modeling of feature distributions, are applied to these image features to create a suite of gait sequence representations. Despite their simplicity, the resulting feature vectors contain enough information to perform well on human identification and gender classification tasks. We demonstrate the accuracy of recognition on gait video sequences collected over different days and times and under varying lighting environments. Each of the integration methods are investigated for their advantages and disadvantages. An improved gait representation is built based on our experiences with the initial set of gait representations. In addition, we show gender classification results using our gait appearance features, the effect of our heuristic feature selection method, and the significance of individual features

Bean sprouts as sources of vitamin C

Typescript, etc.Digitized by Kansas State University Librarie

Determining Annoyance Thresholds of Tones in Noise

Building services equipment often produces noise signatures with significant tones in them that can lead to complaints in the built environment. Previous studies have investigated prominence levels of assorted tonal frequencies, but it is still unclear what prominence of the tones across varying tonal frequencies can lead to human annoyance. This project seeks to apply two different methods towards defining annoyance thresholds of tones in noise at two tonal frequencies: 125 Hz and 500 Hz. In the first, subjects are asked to perform a task, while exposed to ten minutes of a broadband noise spectrum with a specific level of tonal prominence. They are subsequently asked to rate their annoyance to that noise condition. Five prominence levels of each of the two tones are tested above two different background noise levels, for a total of 20 test trials. In the second methodology, subjects listen to each of the two tonal frequencies at a predetermined level above each of the two background noise levels, and then adjust the level of the tone up or down until it becomes just annoying. The strengths, weaknesses, and results obtained for the annoyance thresholds of tones in noise from each of these methods are compared

Object recognition using color and geometry indexing

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.Includes bibliographical references (leaves 76-79).by Lily Lee.M.S

To Open or Not to Open: Developing a COVID-19 Model Specific to Small Residential Campuses

In May 2020, administrators of residential colleges struggled with the decision of whether or not to open their campuses in the Fall semester of 2020. To help guide this decision, we formulated an ODE model capturing the dynamics of the spread of COVID-19 on a residential campus. In order to provide as much information as possible for administrators, the model accounts for the different behaviors, susceptibility, and risks in the various sub-populations that make up the campus community. In particular, we start with a traditional SEIR model and add compartments representing relevant variables, such as quarantine compartments and a hospitalized compartment. We then duplicated the model for ten interacting sub-populations, resulting in a large system of differential equations. The model predicts possible outcomes based on hypothetical administrative policies such as masking, social distancing, and quarantining. As the pandemic developed, we updated the model to account for new policies, such as testing and vaccination and calibrated the model to data gathered from local sources. To complete the modeling process, we describe the parameter-fitting procedure, in which we used publicly available data from the county, as well as specific descriptions of our student body, faculty, and staff. The final stage of the work involved performing numerical simulations and designing an interactive application that allows non-mathematicians to experiment with a range of scenarios. We then extrapolate the findings of our model to a general audience, which along with our plots and app makes model conclusions accessible to all, democratizing the policy-making process