1,720,961 research outputs found
Soft biometric fusion for subject recognition at a distance
No full textThere is societal need for techniques to identify subjects at a distance and when conventional biometrics are obscured, for example in fighting crime. Soft biometrics have this capability and include a subject's height, weight, skin colour and gender. Although the distinctiveness of soft biometric features is intuitively less than that of traditional biometric features, numerous experiments have demonstrated that the desired recognition accuracy can be achieved by using multiple soft biometric features. This paper will propose state-of-the-art multimodal biometric fusion techniques to improve recognition performance of soft biometrics. The key contribution of this paper is the analysis of the influence of distance on soft biometric traits and an exploration of the potency of recognition using fusion at varying distances. A new soft biometric database, containing images of the human face, body and clothing taken at three different distances, was created and used to obtain face, body and clothing attributes. This new database was constructed to explore the suitability of each modality at a distance: intuitively, the face is suitable for near field identification, and the body becomes the optimal choice when the subject is further away. The new dataset is used to explore the potential of face, body and clothing for human recognition using fusion. We present a novel fusion technique at score and rank level that improves identification performance. A novel joint density distribution-based rank-score fusion is also proposed to combine rank and score information. Analysis using the new soft biometric database demonstrates that recognition performance is significantly improved by using the new methods over single modalities at different distances
Soft biometric fusion for subject recognition at a distance
No full textBiometric recognition is an advanced technology that employs physical features (such as fingerprint, iris and face capture) and behavioural features (such as gait, signature and voice) to identify people. Biometric features are reliable and valid ways to describe the unique properties of individuals, but there are often rigorous requirements on the position and characteristics of devices used for data acquisition. Since biometric features can be difficult to capture at a distance, soft biometric features, such as height, weight, skin colour and gender, have received much attention. Although the uniqueness of soft biometric features is not as intuitively obvious as traditional biometric features, numerous experiments have demonstrated that the desired recognition accuracy can be achieved by using different soft biometric features. This thesis will propose state-of-the-art multimodal biometric fusion techniques to improve recognition performance of soft biometrics.The first contribution of this thesis is to estimate fusion performance based on three types of soft biometrics - face, body and clothing. Feature level and score level fusion strategies will be employed to measure and analyse the influence of fusion on soft biometric recognition.The second key contribution of this research is that the analysis of the influence of distance on soft biometric traits and an exploration of the potency of recognition using fusion at varying distances have been performed. A new soft biometric database, containing images of the human face, body and clothing taken at three different distances, was created and used to obtain face, body and clothing attributes. First, this new database was constructed to explore the suitability of each modality at a distance: intuitively, the face is suitable for near field identification, and the body becomes optimal when the subject is further away. The new dataset is used to explore the potential of face, body and clothing for human recognition using fusion. In this section, some novel fusion techniques on different levels (feature, score and rank level) are proposed to improve soft biometric recognition performance.A Supervised Generalised Canonical Correlation (SG-CCA) methodology is proposed to fuse the soft biometric features. The proposed SG-CCA is numerically validated to be the best fusion method compared with other multi-modal fusion methods. An SVM-weighted Likelihood Ratio Test (SVM-LRT) method is proposed for score level fusion. The experimental results demonstrate that SVM-LRT-based fusion significantly outperforms the single-mode recognition. A novel joint density distribution-based rank-score fusion is also proposed to combine rank and score information. Analysis using the new soft biometric database demonstrates that recognition performance is significantly improved by using the new methods over single modalities at different distances
Fusion analysis of soft biometrics for recognition at a distance
No full textThere are many new soft biometric approaches thoughfew are used for identification, especially at a distance. Wecreate a new soft biometric database containing the humanface, body and clothing attributes at three differentdistances. One aim of this paper is to explore the potency offace, body and clothing for human recognition using fusion.Another aim is to explore the suitability for each modalityat a distance: intuitively face is suited to near fieldidentification and body when the subject is further away.The new database and the soft biometric features used areclarified and the influence of distance on soft biometrictraits is investigated. Results show the individualadvantages and disadvantages of face, body and clothingtraits and demonstrate the superiority of fusion method inhuman recognition compared with single-modality.<br/
A joint density based rank-score fusion for soft biometric recognition at a distance
No full textIn order to improve recognition performance, fusion has become a key technique in the recent years. Compared with single-mode biometrics, the recognition rate of multi-modal biometric systems is improved and the final decision is more confident. This paper introduces a novel joint density distribution based rank-score fusion strategy that combines rank and score information. Recognition at a distance has only recently been of interest in soft biometrics. We create a new soft biometric database containing the human face, body and clothing attributes at three different distances to investigate the influence by distance on soft biometric fusion. A comparative study about our method and other state of the art rank level and score level fusion methods are also conducted in this paper. The experiments are performed using a soft biometric database we created. The results demonstrate the recognition performance is significantly improved by our proposed method
Supervised generalized canonical correlation analysis of soft biometric fusion for recognition at a distance
No full textIn order to improve biometric system performance,information fusion becomes a key technique in multi-modalbiometric systems. Multi-modal biometric fusion isconventionally divided into four levels: sensor level, featurelevel, score level and decision level. In this paper, we proposea supervised generalized canonical correlation (sg-CCA)method to fuse soft biometric features. The experiments wereperformed using a soft biometric database which contains thehuman face, body and clothing traits at three different distances.This paper describes the database and analyses the recognitionperformance. Furthermore, it explores the potency of face,body and clothing for human recognition using sg-CCA fusioncompared with other linear dimensionality reduction fusionmethods. The results demonstrate the superiority of softbiometric fusion using sg-CCA method for human recognition.<br/
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Towards automated eyewitness descriptions: describing the face, body and clothing for recognition
No full textA fusion approach to person recognition is presented here outlining the automated recognition of targets from human descriptions of face, body and clothing. Three novel results are highlighted. First, the present work stresses the value of comparative descriptions (he is taller than…) over categorical descriptions (he is tall). Second, it stresses the primacy of the face over body and clothing cues for recognition. Third, the present work unequivocally demonstrates the benefit gained through the combination of cues: recognition from face, body and clothing taken together far outstrips recognition from any of the cues in isolation. Moreover, recognition from body and clothing taken together nearly equals the recognition possible from the face alone. These results are discussed with reference to the intelligent fusion of information within police investigations. However, they also signal a potential new era in which automated descriptions could be provided without the need for human witnesses at all
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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