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Local binary pattern (LBP) is sensitive to noise. LBP projects local patch to eight-dimension vector by operating subtractions between pixel and its neighborhood. Two adjacent pixel values are generally very close, thus little noise can change their relative magnitude, leading to coding err. Using another projecting approach, random projection, as an alternate, we propose local binary pattern based...
There has been significant progress in object part localization such as human pose estimation and facial landmark detection. In most of the previous methods, two phenomena are ignored. Firstly, they usually output a set of candidate pose hypotheses but the hypothesis with the highest score obtained by Non-Maximum Suppression (NMS) is not always the optimal result. Secondly, they can not get exactly...
We present a novel approach to boost image matching performance by fusing multiple local descriptors in the homography space. Traditional matching methods find correspondences based on a single descriptor and the performance becomes unstable due to the goodness of the chosen descriptor To address this problem, our method uses multiple descriptors and select a good descriptor for matching each feature...
Finger vein patterns have been proposed as a suitable biometric feature for authentication applications. Systems using this feature are generally low cost, accurate and easy to use. Such a system is described in this work. Infrared light is used to capture an image of a finger and a pattern recognition algorithm extracts the vein patterns. For robust and precise extraction of the depicted veins, a...
This paper presents a new method for 3D face pose tracking in arbitrary illumination change conditions using color image and depth data acquired by RGB-D cameras (e.g., Microsoft Kinect, Asus Xtion Pro Live, etc.). The method is based on an optimization process of an objective function combining photometric and geometric energy. The geometric energy is computed from depth data while the photometric...
Ranking algorithms have proven the potential for human age estimation. Currently, a common paradigm is to compare the input face with reference faces of known age to generate a ranking relation whereby the first-rank reference is exploited for labeling the input face. In this paper, we proposed a framework to improve upon the typical ranking model, called Voting system on Ranking model (VRank), by...
In this paper, we proposed a new technique for facial expression recognition based on extraction of Complete Robust Local Binary Pattern (CRLBP) features from curvelet domain. The curvelet transform show evidence of improved multiscale directional capability, and a greater ability to localize distributed discontinuities such as edges along curves as compared to traditional multiscale transform such...
Derivation of discriminant features from outstanding face patches has a major role in accurate identification of face expressions. The precise discovery of fragments in the face image improves the confinement of the outstanding patches on face images. Some methods uses a special framework for expression identification by the use of appearance related features of important face patches. A few noticeable...
In this paper, we introduce a two-stage Hand Posture Recognition system using a Kinect sensor. In the first stage, we propose an effective algorithm to segment hand region from complex background, which incorporates both color, depth and skeleton information, without specific requirements on uniform-colored or stable background. It is robust with skin-color noise like arms and face, and can handle...
Facial Capturing cannot ensure the stable head and fix the head position as well as accurate camera distance. This variation degrades the face recognition accuracy. For improving the recognition a true estimator is required to cover the camera distance and the head movement impact. This paper presents a rubber characteristics transformation to generate manifold camera distance and facial shape mapping...
Recognition under uncontrolled lighting conditions remains one of the major challenge for practical face recognition systems. In this work, we present an efficient and effective framework to improve the recognition performance from two aspects: image preprocessing and subspace representation. The step of image preprocessing is mainly used to eliminate the effects of illumination. The step of subspace...
The robust algorithm, which is used for tracking human faces in unconstrained video, is built on Tracking-by-detection based on sparse representation. The algorithm works by combining the advantages of face tracking and face detection to improve the accuracy of tracking face in complex environment. The off-line trained face model fits input image to detect face and online trained tracker localizes...
With the prevalence of camera networks, multi view surveillance video have become commons. Multi view face recognition has become an active research area in recent years. In this paper, an approach for video-based face recognition in camera networks is proposed. Video scenes have unlimited orientation and poses. Video provide an efficient way for feature extraction. The proposed feature is developed...
Recognizing the face of target individuals in a watch-list is among the most challenging applications in video surveillance, especially when enrollment is based on one reference still facial image. Besides the limited representativeness of facial models used for matching, the appearance of faces captured in videos varies due to changes in illumination, pose, scales, etc., and to camera inter-operability...
For traditional mean shift tracking algorithm based on histogram, tracking is failing when target appears under the complicated tracking conditions. It can't significantly distinguish color-similar targets and backgrounds. This thesis proposed a kind of Mean Shift tracking algorithm based on Spatiogram Corrected Background Weighted Histogram and offered detailed derivation of the new algorithm. It...
Most state-of-the-art solutions for localizing facial feature landmarks build on the recent success of the cascaded regression framework [7, 15, 34], which progressively predicts the shape update based on the previous shape estimate and its feature calculation.
In this paper, the Radio-frequency identification (RFID) technology and face recognition are integrated for access control system. A rapid face detection scheme which using a set of rotated haar-like features is adopted for face detection. A normalization process is then applied to adjust the detected faces. The speeded up robust features (SURF) algorithm is used for registering the detected face...
Energy saving is one of the most investigated problems in wireless networks. In this paper, we introduce two homology based algorithms: a simulated annealing one and a robust one. These algorithms optimize the energy consumption at network level while maintaining the maximal coverage. By using simplicial homology, the complex geometrical calculation of the coverage is reduced to simple matrix computation...
Classification with image sets is recently a compelling technique for video-based face recognition. Previous methods in this line mostly assume each image set is pure, i.e., containing well-aligned face images of the same subject, which however is hardly satisfied in real-world applications due to incorrect face detection, questionable tracking, or multiple faces in a single image. This paper proposes...
Gabor features have been used widely in face identification because of their good results and robustness. However, face identification is strongly affected when the test images are very different from those of the gallery, as is the case in varying face pose. In this paper, a new 2D Gabor-based method is proposed that modifies the grid from which the Gabor features are extracted using a mesh to model...
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