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In this paper, we address the problem of shape part recognition. For this purpose, we define a robust distance between shape parts based on geodesics in the shape space. The proposed distance uses an elastic shape matching to handle elastic deformations and compare shape parts locally. This distance is applied to shape part classification and shape part retrieval. An experimental study through the...
Shape outliers can seriously affect the statistical analysis of the shape variations usually performed by the Principal Component Analysis PCA. This paper presents an algorithm for outliers detection and shape restoration as a new strategy for robust statistical shape analysis. The proposed framework is founded on an elastic metric in the shape space to cope with the nonlinear shape variability. The...
Place recognition has been intensively studied in the context of robot vision. BoW-based approach gains its popularity for its efficiency and robustness using features extracted from images. Many features have been examined in the past for place recognition purpose. However, there is no such feature that can outperform others in all environments. Each feature has its own advantage, thus, they should...
This work proposes two different methods for polarity detection in speech and Electroglottograph (EGG) signals using Hilbert Envelope (HE). HE is defined as the magnitude of complex time function and hence an unipolar signal. The zero frequency filtering (ZFF) obtained from HE of LP residual is of same phase for both polarity. Alternatively, the ZFF of speech and EGG, integrated linear prediction...
In today's age of automation, face recognition is a vital component for authorization and security. It has received substantial attention from researchers in various fields of science such as biometrics and computer vision. In this paper, a face recognition system using Principal Component Analysis (PCA) with Back Propagation Neural Networks (BPNN) is analysed. A neural based algorithm is presented...
Questionnaires are widely used for investigation and statistical analysis. However, paper-based questionnaires require great human resources to count the statistical results or enter data into database, which are time consuming. A system capable of recognizing results of questionnaires will be very useful in many aspects. In this paper, we develop a fast and robust digital recognition system for questionnaire...
The aim of this work is to automatically identify and extract the upwelling area in the coastal ocean of Morocco using the satellite observation of chlorophyll concentration. The algorithm starts by the application of FCM algorithm for the purpose of finding regions of homogeneous concentration of the chlorophyll, resulting in c-partitioned labeled images. A region-growing algorithm is then used to...
Recently, nuclear norm based matrix regression (NMR) for classification has been proposed to characterize the whole structure of the error image. However, NMR ignores both the label information and the group structure of training samples. This paper presents a novel yet effective coding scheme called locality-constrained group sparse coding regularized NMR (LGNMR) which not only overcomes these limitations...
Recently sparse and collaborative representation based classification has been developed for face recognition with single sample per person (SSPP). By using variations extracted from a generic training set as an additional common dictionary, promising performance has been reported in face recognition with SSPP. However, existing representation based classifiers for face recognition with SSPP ignored...
Object recognition is a versatile capability. Automatic guided tours and augmented reality are just two examples. Humans seem to do it subconsciously — unaware of the extensive processing required for it — while it is a complex task for machines. Methods based on SIFT features have proven to be robust for recognition. However, a prior detection step is required to limit confusion, caused by, e.g.,...
In recent times, the availability of inexpensive image capturing devices such as smartphones/tablets has led to an exponential increase in the number of images/videos captured. However, sometimes the amateur photographer is hindered by fences in the scene which have to be removed after the image has been captured. Conventional approaches to image de-fencing suffer from inaccurate and non-robust fence...
Image processing-based analysis of microscopic leukocyte helps in early detection of many diseases. It is a challenging issue to segment leukocytes under uneven imaging conditions since features of microscopic leukocyte images change in different labratories. This paper introduces an automatic robust method to segment leukocyte from blood microscopic images using intuitionistic fuzzy divergence based...
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...
In this paper, we propose a fast binary based HMAX model (B-HMAX). In our method, we detect corner based interest points after the second layer C1 to extract fewer numbers of features with better distinctiveness, and use binary string to describe the image patches extracted around detected corners, then use hamming distance for matching between two patches in the third layer S2, which is much faster...
Estimating the location, time and magnitude of a possible earthquake has been the subject of many studies. Various methods have been tried using many input variables such as temperature changes, seismic movements, weather conditions etc. The relation between recorded seismic-acoustic data and occurring an anomalous seismic processes (ASP) has been proved in articles written by Aliev and et al. [1–4]...
The characterization of daily activities using accelerometers is a currently active research field, with special interest on fall detection of elderly people and sports performance. Most works that account walking and running are peak-acceleration based, however, false positives due to artefact acceleration peaks affect the estimation. Also, the proposed algorithms must be simple enough to be implemented...
This paper presents a novel approach for object recognition in extended image databases using a mobile client-server architecture. The proposed approach relies upon feature detection and description to characterize textured objects within the image. The similarity search is performed on descriptor arrays by computing the distance between the query descriptor compared with reference descriptors extracted...
This Keyword queries provide fluent access to data over big databases, but there is problem of low and poor ranking quality or priority problem of obtaining results after querying .To satisfy the user it is necessary to identify the queries that have low ranking quality. In this paper, we are creating a framework to calculate the ratio of degree of difficulty of keyword query on the big databases...
LBP (Local Binary Pattern) is a commonly used operator to extract LBPH (LBP histogram) of an image for local texture description. For gender classification, we proposed an innovative method by extracting multi-scale LBPH in DoG (Difference of Gaussian) space in this paper. Given a facial image, we firstly preprocess it meticulously to avert the local variations of images which probably be caused by...
The earliest research on emotion recognition starts with simulated/acted stereotypical emotional corpus, and then extends to elicited corpus. Recently, the demanding for real application forces the research shift to natural and spontaneous corpus. Previous research shows that accuracies of emotion recognition are gradual decline from simulated speech, to elicited and totally natural speech. This paper...
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