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Signature is a commonly accepted biometric feature for individual identification. On-line signature has begun to prevail in the last decades for it exploits dynamic features which traditional off-line signature fails to preserve. This paper presents a review of researches on on-line signature verification during recent years and lists some of the works that provide promising results.
Biometric gait analysis is to acquire biometric information such as identity, gender, ethnicity and age from people walking patterns. In the walking process, the human body shows regular periodic motion, especially upper and lower limbs, which reflects the individual’s unique movement pattern. Compared to other biometrics, gait can be obtained from distance and is difficult to hide and camouflage...
In the present scenario, Gait descriptors are required to extract the dynamic and static information of the gait. The static and dynamic descriptors are formed from the entire region of the body. We know that majority of dynamic information is in the lower silhouette whereas majority of static information is in the upper silhouette. In our work we have evaluated the significance of dynamic information...
This paper concerns the problem of the effect of emotional change on humans and machines for speaker identification. A contrasting experiment is carried out between Automatic Speaker Identification (ASI) system (applying GMM-UBM and Emotional Factor Analysis (EFA) algorithm) and aural system on emotional speech corpus MASC. The experimental result is similar to that in channel-mismatched condition,...
Emotion variability is an important factor that degrades the performce of speaker recognition system. This paper borrows ideas from Joint Factor Analysis (JFA) algorithm based on the similarity between emotion effect and channel effect and develops Emotional Factor Analysis (EFA) into solving the emotion variability problem. I-Vector is appiled also. The experiment carried on MASC (Madarin Affective...
The paper proposes the sub-band main peak frequencies( SMPF) for speaker identification (SI). The SMPF could be derived from the sub-band first formant frequencies by all-pole model of speech signal. Compared with MFCC features for SI based on a Gaussian mixture model (GMM), only SMPF features for SI is better than only the MFCC, with one of improved relative rate up to 15%. Experimental utterances...
As an emerging field of speech recognition, dialect identification plays an important role for promoting applications of speech recognition technology. Since the communications among Mainland China, Hong Kong and Taiwan are becoming frequently, it is particularly necessary to identify their dialects. This paper makes contributions to this issue in the following three-folds: 1) we build a speech corpus...
Face recognition in videos is a hot topic in computer vision and biometrics over many years. Compared to traditional face analysis, video based face recognition has advantages of more abundant information to improve accuracy and robustness, but also suffers from large scale variations, low quality of facial images, illumination changes, pose variations and occlusions. Related to applications, we divide...
A novel local feature descriptor, namely Directional Local Binary Patterns (DLBP), was proposed in this paper and applied for face recognition. The descriptor first extracts directional edge information, then codes these information using Local Binary Patterns (LBP). When applied for face recognition, a face image is divided into a number of small sub-windows, DLBP histogram extracted from each sub-window...
This paper develops a novel method named image decomposition based on locally adaptive regression kernels (ID-LARK) for feature extraction. ID-LARK is robust to variations of illumination, since it decomposes the local features into different sub-images. And they describe the structure information hidden in the unobserved space. More specially, ID-LARK first exploits local structure information by...
The algorithm of 105 facial feature points localization has been proposed in [1]. In this paper, we studied the stability of these feature points in different photos of the same person, and then we presented an improved face recognition system using these facial feature points to perform face recognition and check duplicate entries in database. All of these analyses and experiments are performed on...
A good face recognition algorithm should be robust against variations caused by occlusion, expression or aging changes etc. However, the performance of holistic feature based methods would drop dramatically as holistic features are easily distorted by those variations. SIFT, a classical sparse local feature descriptor, was proposed for object matching between different views and scales and has its...
It has been known that it is hard to capture the high-frequency components (shadows and specularities) during the modeling of illumination effects. In this paper, we propose a reflectance model to simulate the interaction of light and the facial surface under the assumption that face is strictly axial symmetry. This model works well not only in fitting the intensities of pixel but also in processing...
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