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Since the hyperspectral images (HSI) could provide much more useful discriminative information that cannot be obtained by the conventional imaging techniques, the hyper-spectral imaging technology was widely used in remote sensing area and recently used in many other aspects, such as the biological images recognition. However, most of the time, the size of hyperspectral data is so large that to process...
This paper presents our system designed for MSR-Bing Image Retrieval Challenge @ ICME 2014. The core of our system is formed by a text processing module combined with a module performing PCA-assisted perceptron regression with random sub-space selection (P2R2S2). P2R2S2 uses Over-Feat features as a starting point and transforms them into more descriptive features via unsupervised training. The relevance...
Recent years have witnessed a growing interest in developing methods for 3D face recognition. However, 3D scans often suffer from the problems of missing parts, large facial expressions, and occlusions. In this paper, we propose a novel general approach to deal with the 3D face recognition problem by making use of multiple keypoint descriptors (MKD) and the sparse representation-based classifier (SRC)...
Although the KISSME approach can effectively reduce the correlation between feature vectors of samples, it can't restrain the multimodal distribution of vectors in the global level. This drawback brings negative impact on classification performance. Inspired by KISSME, we propose our fusion algorithm of Likelihood Ratio Test and cosine similarity for large scale face verification (CS-KISSME). In our...
The current popular image features index structure can be divided into tree-based structures, hash-based structures and machine learning based structures. In face recognition, selecting the appropriate image feature indexing structure to achieve large-scale face image matching has aways been a problem. In this paper, we present a global image features indexing method based on complete binary tree,...
This paper presents an integrated security management for authentication of users based on dynamic biometric features. For the vary applications of mobile-commerce, a mobile device cooperating with a user calibration interface is used to capture the dynamic face images of the sliding view of the human face to improve the security level of the whole system. The dynamic face recognition automatically...
A problem of controlling a group of independent identical agents is considered. Such problems arise in mathematical economics, in robotics (swarms of mini-robots). The model includes a stochastic component. The general method of the Bellman equation [6] cannot be applied to this problem. The solution is found by the comparison method for solutions of SDE using the technique of the Skorokhod reflection...
Investigating that some face regions are possibly more reliable than the others when verifying two face images due to the local abnormal differences caused by the uncontrolled factors in unconstrain environment,we propose a novel face verification algorithm based on pairwise pre-estimation. In our algorithm, we estimate the reliability of a face region by detecting abnormal differences on some key...
The driver's head pose plays a very important role in risk prediction of vehicle driving. Head pose affects the driver's ability to observe the driving environment, and determines the safety in the process of driving. This paper proposes an efficient representation and feature extraction technique for head pose estimation of the driver. This method 1firstly applies SIFT algorithm to extracting the...
Lifting as geometric operation can be defined as a pseudo-inverse of orthogonal projection. It has received attention in different fields and applications (mechanics, geometry, control, etc). Numerous studies have been dedicated to the existence conditions of a convex lifting in a higher dimension for a given cell complex. It is worth noting that this notion can be extended for a polyhedral partition...
On the basis of research for sparse representation and Gabor wavelet, a new method for face recognition combined Gabor with representation is proposed in this paper. Gabor wavelet transformation is used for face image from the training image set to obtain facial features, the over-complete dictionary is built by the Gabor features from all training set, and the sparse facial feature is obtained by...
Face recognition and verification is still a challenging problem due to several issues such as pose, facial expression, occlusion, imaging conditions, rotation, size and orientation. This paper addresses the problem of recognizing human faces despite the presence in pose and size variation. To handle these problems, we mainly focus on block size definition. Instead of uniform block we thus propose...
High dimension of the features employed for face recognition is the main reason to slow down the recognition speed. Additionally, selecting salient facial features has significant impact on the efficiency of face recognition. In order to get the sparse and salient facial features, this paper propose a new sparse learning approach for salient facial feature description. This approach is to learn the...
The human interaction based framework for manipulable object categorization is proposed in this paper. In the proposed framework, co-occurrence and spatial relationship based features are developed to improve the categorization problem of the objects with high intra-class variation, deformable objects or the objects that are occluded. The descriptor in this framework is based on a co-occurrence of...
De-Identification is a process which can be used to ensure privacy by concealing the identity of individuals captured by video surveillance systems. One important challenge is to make the obfuscation process reversible so that the original image/video can be recovered by persons in possession of the right security credentials. This work presents a novel Reversible De-Identification method that can...
Non-negative Matrix Factorization (NMF) algorithm and its variations have been successfully applied to many fields, but how to set the characteristic dimension value and the sparse factors value to improve recognition accuracy has been puzzling the researchers. Until now, it is regretful that the rigorous algorithm doesn't appear. The purpose of this paper is not to improve existing NMF algorithm...
In this paper, it is shown that Local Zernike Moments which is used in object and face recognition applications succesfully, can also used for face-pair matching problem. In this study, instead of using feature vectors produced by LZM directly, we focussed on reducing the dimensions of feature vectors and increasing the performance. In the light of experimental results, a new method called L2ML-YZM...
Glasses detection is one of attractive tasks in image processing since it increases the performance of face recognition systems. In this study, we aimed to detect the glasses on face images automatically. In order to do this, we trained a classifier with Labelled Faces in the Wild Home(LFW) dataset to decide whether a person wear glasses or not on face images. Before classification process, image...
In this paper, a feature combining method which can be used in gender classification has been proposed. This method is based on examinating the importance of the pixel regions on face images. In this study, after the analysing commonly used three feature extraction methods (Local binary patterns, discrete cosine transform, histogram of oriented gradients) dimension reduction is achieved via eliminating...
The performance of a face recognition system is negatively affected by the accessories used on the face. Like many methods, the recognition performance of the Common Vector Approach (CVA) [1] over occluded images is not at the desired level. In this work, we proposed an extension of the CVA, namely the Modular Common Vector Approach (M-CVA), which improves the recognition performance at the occluded...
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