Detection based low frame rate human tracking

Tracking by association of low frame rate detection responses is not trivial, as motion is less continuous and hence ambiguous. The problem becomes more challenging when occlusion occurs. To solve this problem, we firstly propose a robust data association method that explicitly differentiates ambiguous tracklets that are likely to introduce incorrect linking from other tracklets, and deal with them effectively. Secondly, we solve the long-time occlusion problem by detecting inter-track relationship and performing track split and merge according to appearance similarity and occlusion order. Experiment on a challenging human surveillance dataset shows the effectiveness of the proposed method. © 2010 IEEE.published_or_final_versionThe 20th International Conference on Pattern Recognition (ICPR 2010), Istanbul, Turkey, 23-26 August 2010. In Proceedings of 20th ICPR, 2010, p. 3529-353

Метод обнаружения искусственного изменения папиллярных узоров отпечатков пальцев на основе когерентности поля ориентаций

Одной из актуальных проблем, связанных с безопасностью биометрических технологий, является обнаружение фальшивых и подвергшихся искусственному изменению папиллярных узоров (ИИПУ) отпечатков пальцев. Разработан эффективный метод обнаружения ИИПУ отпечатков пальцев на основе модифицированной модели когерентности поля ориентаций. Результаты экспериментов показывают, что метод хорошо выявляет изображения ИИПУ отпечатков пальцев. Предложенный метод не требует дополнительной обработки и использует результаты вычислений в традиционных блоках существующих систем распознавания отпечатков пальцев.Широке застосування біометричних технологій виявляє різні проблеми, пов’язані з їх безпекою. Однією з актуальних проблем є виявлення фальшивих і таких, що зазнали штучних змін, папілярних візерунків відбитків пальців. Розроблено ефективний метод виявлення штучної зміни папілярних візерунків відбитків пальців на основі модифікованої моделі когерентності поля орієнтацій. Результати експериментів показують, що метод добре виявляє зображення штучної зміни папілярних візерунків відбитків пальців. Запропонований метод не вимагає додаткової обробки і використовує результати обчислень в традиційних блоках існуючих систем розпізнавання відбитків пальців.Widespread use of biometric technologies determines various problems related to their security. One of the important problems is detection of forged and altered fingerprints. An efficient method for altered fingerprints detection on the basis of the modified model of the orientation field coherence is discovered. The results of experiments show that the method detects altered fingerprints well. The proposed method does not require additional processing resources and it uses the results of the traditional blocks of existing fingerprint recognition systems

Visual Gaze Estimation by Joint Head and Eye Information

International audienc

Towards a continuous biometric system based on ECG signals acquired on the steering wheel

Electrocardiogram signals acquired through a steering wheel could be the key to seamless, highly comfortable, and continuous human recognition in driving settings. This paper focuses on the enhancement of the unprecedented lesser quality of such signals, through the combination of Savitzky-Golay and moving average filters, followed by outlier detection and removal based on normalised cross-correlation and clustering, which was able to render ensemble heartbeats of significantly higher quality. Discrete Cosine Transform (DCT) and Haar transform features were extracted and fed to decision methods based on Support Vector Machines (SVM), k-Nearest Neighbours (kNN), Multilayer Perceptrons (MLP), and Gaussian Mixture Models – Universal Background Models (GMM-UBM) classifiers, for both identification and authentication tasks. Additional techniques of user-tuned authentication and past score weighting were also studied. The method’s performance was comparable to some of the best recent state-of-the-art methods (94.9% identification rate (IDR) and 2.66% authentication equal error rate (EER)), despite lesser results with scarce train data (70.9% IDR and 11.8% EER). It was concluded that the method was suitable for biometric recognition with driving electrocardiogram signals, and could, with future developments, be used on a continuous system in seamless and highly noisy settings.info:eu-repo/semantics/publishedVersio

Extraction and selection of muscle based features for facial expression recognition

In this study we propose a new set of muscle activity based features for facial expression recognition. We extract muscular activities by observing the displacements of facial feature points in an expression video. The facial feature points are initialized on muscular regions of influence in the first frame of the video. These points are tracked through optical flow in sequential frames. Displacements of feature points on the image plane are used to estimate the 3D orientation of a head model and relative displacements of its vertices. We model the human skin as a linear system of equations. The estimated deformation of the wireframe model produces an over-determined system of equations that can be solved under the constraint of the facial anatomy to obtain muscle activation levels. We apply sequential forward feature selection to choose the most descriptive set of muscles for recognition of basic facial expressions.Publisher's VersionAuthor Post Prin

Preface

[No abstract available