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The gesture recognition has raised attention in computer vision owing to its many applications. However, video-based large-scale gesture recognition still faces many challenges, since many factors like background may disturb the accuracy. To achieve gesture recognition with large-scale videos, we propose a method based on RGB-D data. To learn gesture details better, the inputs are expanded into 32-frame...
In this paper is presented a novel multimodal emotion recognition system which is based on the analysis of audio and visual cues. MFCC-based features are extracted from the audio channel and facial landmark geometric relations are computed from visual data. Both sets of features are learnt separately using state-of-the-art classifiers. In addition, we summarise each emotion video into a reduced set...
A novel approach for fast iris recognition on mobile devices is presented in this paper. Its key features are: (i) the use of a combination of classifiers exploiting the iris colour and texture information; (ii) its limited computational time, particularly suitable for fast identity checking on mobile devices; (iii) the high parallelism of the code, making this approach also appropriate for identity...
This paper describes iris biometric matching performed using the iris pictures captured by the standard visible spectrum smart phone cameras from the MICHE II database. Our method uses a combination of a popular iris code approach and a periocular biometric based on the Multi-Block Transitional Local Binary Patterns. The authentication scores are calculated separately, and the results are combined...
Current research of emotion recognition from electroencephalogram (EEG) signals rarely considers common patterns embodied in multiple subjects and individual patterns for each subject simultaneously. Therefore, in this paper, we propose a novel emotion recognition approach using subjects or subject groups as privileged information, which is only available during training. First, five frequency features...
This paper proposes an object verification method by using sparse representation (SR) which has been applied for object representation and recognition. However, SR dictionary does not show sufficient compactness. Our method comprises three major modules. First, we train the sparse matrix by using boost K-Singular Value Decomposition (boost K-SVD) to obtain a sparse vector set. Second, we combine two...
GAT (Global Affine Transformation) and GPT (Global Projection Transformation) correlation matchings were successively proposed by Wakahara and Yamashita which use affine transformation (AT) and 2D projection transformation (PT), respectively, to maximize the normalized cross-correlation value between a template and a GAT/GPT-superimposed input image. In theory, to maximize the degree of matching via...
The problems of hand detection have been widely addressed in many areas, e.g. human computer interaction environment, driver behaviors monitoring, etc. However, the detection accuracy in recent hand detection systems are still far away from the demands in practice due to a number of challenges, e.g. hand variations, highly occlusions, low-resolution and strong lighting conditions. This paper presents...
Inferring scene depth from a single monocular image is an essential component in several computer vision applications such as 3D modeling and robotics. This process is an ill-posed problem. To tackle this challenging problem, previous efforts have been focusing on exploiting only global or local depth aware properties. We propose a model that incorporates both of them to obtain significantly more...
Fingerprint classification is an effective technique for reducing the candidate numbers of fingerprints in the stage of matching in automatic fingerprint identification system (AFIS). In recent years, deep learning is an emerging technology which has achieved great success in many fields, such as image processing, computer vision. In this paper, we have a preliminary attempt on the traditional fingerprint...
Improving accuracy of matching fingerprint images acquired from two different fingerprint sensors is an important research problem with several promising studies in the literature. Most of these studies focus on sensor interoperability using fingerprints acquired from different kinds of contact-based sensors. However emerging contactless fingerprint technologies have shown its benefits. This paper...
We propose a novel geometric framework for analyzing spontaneous facial expressions, with the specific goal of comparing, matching, and averaging the shapes of landmarks trajectories. Here we represent facial expressions by the motion of the landmarks across the time. The trajectories are represented by curves. We use elastic shape analysis of these curves to develop a Riemannian framework for analyzing...
Categorical description of leaf shapes is of paramount importance in agriculture and plant sciences. Traditionally, these descriptions have been based on categorical systems proposed by domain experts. Despite the importance of these visual descriptive systems, these approaches may be limited by the representation of unknown shapes as expected in exploratory domains. In this work, we propose a novel...
Biometric systems can be attacked in several ways and the most common being spoofing the input sensor. Therefore, anti-spoofing is one of the most essential prerequisite against attacks on biometric systems. For face recognition it is even more vulnerable as the image capture is non-contact based. Several anti-spoofing methods have been proposed in the literature for both contact and non-contact based...
Fish recognition and identification in an underwater environment are important research topics. In this study, several real-world underwater videos were collected to construct a fish category database for further fish recognition and identification. Recently, compressive sensing, using reconstruction algorithms to reconstruct a sparse signal, has been successfully applied to face recognition. Reconstruction...
Voiceprint based identity authentication system (IAS) for smartphone users is highly demanded in mobile internet times. There are some successful application cases for English smartphone users. However, to our knowledge, the research outcomes are few for Mandarin smartphone users. Analysis shows that there remain some issues need to be carefully considered: (1) security issue: vulnerable to replay...
A new online handwritten Mongolian word database, MRG-OHMW, is introduced in this paper. This database contains 946 Mongolian words produced by 300 persons from Mongolian ethnic minority. These Mongolian words are composed of one to fourteen Mongolian characters, and selected from large-scale Mongolian text corpus according to the frequencies of usage. The current version of this database is collected...
Overlapped handwriting recognition is widely used to input text in smart devices since it allows to write continuous characters on an size-restricted screens. How to segment the stroke sequences into characters is a crucial step before recognition. It is currently formulated as a two-class classification problem merely evaluating on the relationships between a pair of adjacent strokes. To facilitate...
Human age estimation is an important research topic and can find its applications in such as commodity recommendation and security monitoring. The establishment of existing estimators basically follows a same pipeline, i.e., an estimator is built from a given training dataset like FG-NET and then evaluated on a holdout testing set to determine its effectiveness. In doing so, a usually-followed assumption...
In this paper, we present a new approach for periocular recognition based on the Symmetry Assessment by Feature Expansion (SAFE) descriptor, which encodes the presence of various symmetric curve families around image key points. We use the sclera center as single key point for feature extraction, highlighting the object-like identity properties that concentrates to this unique point of the eye. As...
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