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Identity masking methods have been developed in recent years for use in multiple applications aimed at protecting privacy. There is only limited work, however, targeted at evaluating effectiveness of methods–with only a handful of studies testing identity masking effectiveness for human perceivers. Here, we employed human participants to evaluate identity masking algorithms on video data of drivers,...
This paper explores the difficulty of performing automatic demographic prediction on the East Asian population. We introduce the Wild East Asian Face Dataset (WEAFD), a new and unique dataset, to the research community. This dataset consists primarily of labeled face images of individuals from East Asian countries, including Vietnam, Burma, Thailand, China, Korea, Japan, Indonesia, and Malaysia. East...
Automatic recognition systems are valuable tools for identifying unknown deceased individuals. Immediately after death, fingerprint and face biometric samples are easy to collect using standard sensors and can be easily matched to antemortem biometric samples. Even though early postmortem fingerprints and facial images have been used for identification purposes for decades, there are no studies that...
Modern vision systems are often a heterogeneous collection of image processing, machine learning, and pattern recognition techniques. One problem with these systems is finding their optimal parameter settings, since these systems often have many interacting parameters. This paper proposes the use of a Genetic Algorithm (GA) to automatically search parameter space. The technique is tested on a publicly...
The CSU Face Identification Evaluation System provides standard face recognition algorithms and standard statistical methods for comparing face recognition algorithms. The system includes standardized image pre-processing software, three distinct face recognition algorithms, analysis software to study algorithm performance, and Unix shell scripts to run standard experiments. All code is written in...
FaceL is a simple and fun face recognition system that labels faces in live video from an iSight camera or webcam. FaceL presents a window with a few controls and annotations displayed over the live video feed. The annotations indicate detected faces, positions of eyes, and after training, the names of enrolled people. Enrollment is video based, capturing many images per person. FaceL does a good...
Inexpensive “point-and-shoot” camera technology has combined with social network technology to give the general population a motivation to use face recognition technology. Users expect a lot; they want to snap pictures, shoot videos, upload, and have their friends, family and acquaintances more-or-less automatically recognized. Despite the apparent simplicity of the problem, face recognition in this...
We investigate the existence of quality measures for face recognition. First, we introduce the concept of an oracle for image quality in the context of face recognition. Next we introduce greedy pruned ordering (GPO) as an approximation to an image quality oracle. GPO analysis provides an estimated upper bound for quality measures, given a face recognition algorithm and data set. We then assess the...
Accurately measuring the location of facial features is an important step in many face recognition algorithms. Every face is unique which means localization needs to be tolerant of differences between individual subjects. Additionally, changing illumination, poor focus, and deformation due to expression changes complicate the problem. This paper introduces a method for locating facial features that...
Several studies have shown the existence of biometric zoos. The premise is that in biometric systems people fall into distinct categories, labeled with animal names, indicating recognition difficulty. Different combinations of excessive false accepts or rejects correspond to labels such as: Goat, Lamb, Wolf, etc. Previous work on biometric zoos has investigated the existence of zoos for the results...
Although not commonly used, correlation filters can track complex objects through rotations, occlusions and other distractions at over 20 times the rate of current state-of-the-art techniques. The oldest and simplest correlation filters use simple templates and generally fail when applied to tracking. More modern approaches such as ASEF and UMACE perform better, but their training needs are poorly...
A study is presented showing how three state-of-the-art algorithms from the Face Recognition Vendor Test 2006 (FRVT 2006) are effected by factors related to face images and people. The recognition scenario compares highly controlled images to images taken of people as they stand before a camera in settings such as hallways and outdoors in front of buildings. A Generalized Linear Mixed Model (GLMM)...
This paper presents a bimodal identification system using text based term vectors and EBGM face recognition. Identification was tested on a database of 118 celebrities downloaded from the internet. The dataset contained multiple images and two biographies for each person. Text based identification had a 100% identification rate for the full biographies. When the text data was artificially restricted...
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