Face Recognition using 3D Facial Shape and Color Map Information: Comparison and Combination

In this paper, we investigate the use of 3D surface geometry for face recognition and compare it to one based on color map information. The 3D surface and color map data are from the CAESAR anthropometric database. We find that the recognition performance is not very different between 3D surface and color map information using a principal component analysis algorithm. We also discuss the different techniques for the combination of the 3D surface and color map information for multi-modal recognition by using different fusion approaches and show that there is significant improvement in results. The effectiveness of various techniques is compared and evaluated on a dataset with 200 subjects in two different positions.Comment: Proceedings of SPIE Vol. 5404 Biometric Technology for Human Identification, Anil K. Jain; Nalini K. Ratha, Editors, pp.351-361, ISBN: 9780819453273 Date: 25 August 200

Coping responses among aged home health care clients : a qualitative study

As people age, they are faced with roles and activities that challenge their intellectual or physical capabilities. People, however, are pragmatic by nature; they seek to use what works when faced with predicaments that test their mettle. The purpose of this research has been to understand how aged home health care clients try to maintain valued selves in the face of their declining functional abilities. Data were drawn from qualitative methodological techniques (e.g., participant observation, observational data, and unstructured interviews). In order to provide some structure to this data, a theoretical orientation grounded in symbolic interaction was used in lieu of activity theory, mainly because of activity theory\u27s inability to get at older persons\u27 definitions of the situation (or, what it is like to be old and debilitated from the perspectives of the older persons themselves). A review of the literature revealed important information concerning: (a) adaptation techniques used by older and chronically ill persons, and (b) differing opinions of disease, health, and life satisfaction that exist among older and chronically ill persons, their doctors, and social workers. The Social Histories served as a backdrop to the Findings chapter, which focused on: (a) descriptive accounts of day-to-day activities; (b) feelings of illness and isolation; and (c) coping/adaptation responses used by aged home health care clients as they attempted to maintain/preserve positive images of self, despite limitations in functioning. In conclusion, my aged subjects not only replaced their declining abilities with others that were less demanding, but they also-without apparent reflection-were able to maintain positive images of self by virtue of their participation in activities and roles that made them feel confident and competent

Physid Snails as Sentinels of Freshwater Nematomorphs

Freshwater nematomorphs, or gordiids, are parasitic as larvae, but free-living in aquatic environments as adults. Studies based on the collection of adults have reported gordiids to be widespread, but discontinuous in distribution. However, a relatively short adult life span and unknown life history make the detection of adults difficult. An alternative approach to investigate gordiid distribution is to use cysts. Of all paratenic hosts, snails were chosen because they lacked internal defense reactions to the cysts and become easily infected. Here, it is reported that the occurrence of gordiids on the basis of the cyst stage is much more common than previously reported, thus altering the perception of how common these worms are. Using this modified survey procedure, gordiid cysts were found at 70% of sites examined, in an area where extensive sampling over 3 yr yielded adults only at a single site. Of 1,000 snails dissected, 395 were infected with gordiids (intensity range: 1-465). Furthermore, different types of human-modified landscapes did not affect gordiid distribution, suggesting that as urban and suburban areas sprawl, human encounters or pseudoparasitism with nematomorphs may increase. The results of this study indicate that use of organismal-specific sampling techniques can be critical in studies of parasite distribution and biodiversity

Physid Snails as Sentinels of Freshwater Nematomorphs

Freshwater nematomorphs, or gordiids, are parasitic as larvae, but free-living in aquatic environments as adults. Studies based on the collection of adults have reported gordiids to be widespread, but discontinuous in distribution. However, a relatively short adult life span and unknown life history make the detection of adults difficult. An alternative approach to investigate gordiid distribution is to use cysts. Of all paratenic hosts, snails were chosen because they lacked internal defense reactions to the cysts and become easily infected. Here, it is reported that the occurrence of gordiids on the basis of the cyst stage is much more common than previously reported, thus altering the perception of how common these worms are. Using this modified survey procedure, gordiid cysts were found at 70% of sites examined, in an area where extensive sampling over 3 yr yielded adults only at a single site. Of 1,000 snails dissected, 395 were infected with gordiids (intensity range: 1-465). Furthermore, different types of human-modified landscapes did not affect gordiid distribution, suggesting that as urban and suburban areas sprawl, human encounters or pseudoparasitism with nematomorphs may increase. The results of this study indicate that use of organismal-specific sampling techniques can be critical in studies of parasite distribution and biodiversity

Demographic Bias: A Challenge for Fingervein Recognition Systems?

Recently, concerns regarding potential biases in the underlying algorithms of many automated systems (including biometrics) have been raised. In this context, a biased algorithm produces statistically different outcomes for different groups of individuals based on certain (often protected by anti-discrimination legislation) attributes such as sex and age. While several preliminary studies investigating this matter for facial recognition algorithms do exist, said topic has not yet been addressed for vascular biometric characteristics. Accordingly, in this paper, several popular types of recognition algorithms are benchmarked to ascertain the matter for fingervein recognition. The experimental evaluation suggests lack of bias for the tested algorithms, although future works with larger datasets are needed to validate and confirm those preliminary results.Comment: 5 pages, 2 figures, 8 tables. Submitted to European Signal Processing Conference (EUSIPCO) -- special session on bias in biometric

Mobile device reference apps to monitor and display biomedical information

Master of ScienceDepartment of Electrical and Computer EngineeringSteven WarrenSmart phones and other mobile technologies can be used to collect and display physiological information from subjects in various environments – clinical or otherwise. This thesis highlights software app reference designs that allow a smart phone to receive, process, and display biomedical data. Two research projects, described below and in the thesis body, guided this development. Android Studio was chosen to develop the phone application, after exploring multiple development options (including a cross-platform development tool), because it reduced the development time and the number of required programming languages. The first project, supported by the Kansas State University Johnson Cancer Research Center (JCRC), required a mobile device software application that could determine the hemoglobin level of a blood sample based on the most prevalent color in an image acquired by a phone camera, where the image is the result of a chemical reaction between the blood sample and a reagent. To calculate the hemoglobin level, a circular region of interest is identified from within the original image using image processing, and color information from that region of interest is input to a model that provides the hemoglobin level. The algorithm to identify the region of interest is promising but needs additional development to work properly at different image resolutions. The associated model also needs additional work, as described in the text. The second project, in collaboration with Heartspring, Wichita, KS, required a mobile application to display information from a sensor bed used to gather nighttime physiological data from severely disabled autistic children. In this case, a local data server broadcasts these data over a wireless network. The phone application gathers information about the bed over this wireless network and displays these data in user-friendly manner. This approach works well when sending basic information but experiences challenges when sending images. Future work for both project applications includes error handling and user interface improvements. For the JCRC application, a better way to account for image resolution changes needs to be developed, in addition to a means to determine whether the region of interest is valid. For the Heartspring application, future work should include improving image transmissions

Evaluation of Pattern Classifiers for Fingerprint and OCR Applications

(Also cross-referenced as CAR-TR-691) In this paper we evaluate the classification accuracy of four statistical and three neural network classifiers for two image based pattern classification problems. These are fingerprint classification and optical character recognition (OCR) for isolated handprinted digits. The evaluation results reported here should be useful for designers of practical systems for these two important commercial applications. For the OCR problem, the Karhunen-Loeve (K-L) transform of the images is used to generate the inp ut feature set. Similarly for the fingerprint problem, the K-L transform of the ridge directions is used to generate the input feature set. The statistical classifiers used were Euclidean minimum distance, quadratic minimum distance, normal, and knearest neighbor. The neural network classifiers used were multilayer perceptron, radial basis function, and probabilistic. The OCR data consisted of 7,480 digit images for training and 23,140 digit images for testing. The fingerprint data consisted of 9,000 trai ning and 2,000 testing images. In addition to evaluation for accuracy, the multilayer perceptron and radial basis function networks were evaluated for size and generalization capability. For the evaluated datasets the best accuracy obtained for either pro blem was provided by the probabilistic neural network, where the minimum classification error was 2.5% for OCR and 7.2% for fingerprints