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Many computer vision applications adopting consumer depth cameras have recently received much attention due to the availability at low prices and the potential benefits to provide more useful information, which can result in a higher accuracy (e.g., for object recognition). In this work, to address the problem of drinking activity recognition in vision-based Ambient Assisted Living by using depth...
Palmprint is a reliable and unique biometric trait with high acceptability. In this paper, we propose a new Local Composition Derivative Pattern (LCDP) for palmprint recognition. LCDP extracts first order derivative information of images along radial and directional directions which can capture more detailed information than the non-directional local binary pattern (LBP). Different from LBP encoding...
In various real-world applications of distributed and multi-view vision systems, the ability to learn unseen actions in an online fashion is paramount, as most of the actions are not known or sufficient training data is not available at design time. We propose a novel approach which combines the unsupervised learning capabilities of Hierarchical Dirichlet Processes (HDP) with Temporal Self-Similarity...
Crowd density estimation is important for intelligent video surveillance. Many methods based on texture features have been proposed to solve this problem. Most of the existing algorithms only estimate crowd density on the whole image while ignore crowd density in local region. In this paper, we propose a novel texture descriptor based on Local Binary Pattern (LBP) Co-occurrence Matrix (LBPCM) for...
In this paper, a palmprint identification and verification approach based on Pyramidal Histograms of Oriented Gradients (PHOG) and fast tree based matching is presented. In the feature extraction stage, proposed local histograms of oriented gradient are extracted in each level or scale of the Gaussian pyramid of the palmprint. This matter helps to extract high contrast and reliable lines. In the identification...
Representing a video by a set of key frames is useful for efficient video browsing and retrieving. But key frame extraction keeps a challenge in the computer vision field. In this paper, we propose a joint framework to integrate both shot boundary detection and key frame extraction, wherein three probabilistic components are taken into account, i.e. the prior of the key frames, the conditional probability...
In this paper we apply nonlinear signal analysis to a music information retrieval task. More concretely, we apply the concept of recurrence plots and recurrence histograms to extract information from music audio frames. We evaluate the effectiveness of this approach with a typical genre classification framework and compare it against a baseline obtained from standard spectrum-based descriptors. The...
Efficient data mining and indexing is important for multimedia analysis and retrieval. In the field of large-scale video analysis, effective genre categorization plays an important role and serves one of the fundamental steps for data mining. Existing works utilize domain-knowledge dependent feature extraction, which is limited from genre diversification as well as data volume scalability. In this...
In this paper, a three tier strategy is suggested to recognize the hand-printed characters of Devanagari script. In primary and secondary stage classification, the structural properties of the script are exploited to avoid classification error. The results of all the three stages are reported on two classifiers i.e. MLP and SVM and the results achieved with the later are very good. The performance...
Firstly, the Harris corner detector is improved to detect feature points and the method to describe the features of the points with SIFT (scale invariant feature transform) is enhanced. Secondly, Euclidian distance is utilized to get exact matching in the point set above. Finally, a simple efficient way to eliminate wrong matches is given. This method is proved to meet the needs of real-time binocular...
In the field of unsupervised texture classification, a combination of various families of methods was usually used for better classification results. However, the existing methods are usually used for specific application and evaluated with fixed window size. In this literature, we propose an effort to combine multi-scale features for unsupervised texture classification. The local binary pattern (LBP)...
We propose a simple approach to fast extract the main text content from Web pages, especially online news pages. Most existing approaches need to construct the DOM tree structure from the HTML source of the Web page first, and then, extract the important content by pruning/merge the DOM branches/sub-trees. Such DOM tree processing tasks are very time-consuming. Our solution processes the HTML source...
It becomes an emergent challenge how to retrieve the cloud image from a gigantic cloud image database because of the fast accumulation of digital cloud images in meteorological area. This paper puts forward the histogram descriptor based on gray level co-occurrence matrices to depict the texture characteristics of cloud images, and then applies the histogram descriptor in content-based cloud image...
Virtual boundary (tripwire) crossing detection is an essential component in almost all modern digital visual surveillance systems. In this paper, we address the problem of achieving reliable tripwire crossing results in crowded scenarios and propose a new technique for the replacement of conventional tracking based tripwire techniques. We introduce the concept of "ground patches" which are...
According to the characters of the menology and combining with the advantages of two matching methods, a new method of feature-constrained area matching is proposed. In the preprocessing part, the original images are processed by histogram equalization algorithm in order to increase the contrast, enhance the texture character and satisfy the needs of feature-based matching. In the feature-based matching...
Signature zones' identification has been used in signature recognition and verification. The identification of an offline signature requires the whole image of the signature to be processed without considering other features in the signature. One of the signature features that are frequently used as the precondition for other subsequent algorithms in signature recognition and verification is the baseline...
Automatic online and offline signature recognition and verification is becoming ubiquitous in person identification and authentication problems, in various domains requiring different levels of security. There has recently been an increasing interest in developing such systems, with several views on which are the best discriminator features. This paper presents a new offline signature verification...
We present a novel method for fusing different classifiers outputs. Our approach, called Context Extraction for Local Fusion with Feature Discrimination (CELF-FD), is a local approach that adapts the fusion method to different regions of the feature space. It is based on a novel objective function that combines context identification and multi-algorithm fusion criteria into a joint objective function...
A two-stage approach for word-wise identification of English (Roman), Devnagari and Bengali (Bangla) scripts is proposed. This approach balances the tradeoff between recognition accuracy and processing speed. The 1st stage allows identifying scripts with high speed, yet less accuracy when dealing with noisy data. The advanced 2nd stage processes only those samples that yield low recognition confidence...
Multispectral microscopy for applications in histology and cytology has attracted much attention in recent years. It has been shown that the unique transmission spectra of biological tissue provides additional information that is potentially useful for better classification of the pathologies. However, irrelevant features in multispectral data may affect results and performance of data analysis methods...
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