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Object recognition technology is an important research field of image understanding and computer vision, with its wide range of application, it attracts more and more attention. HMAX was proposed as a simple and biologically feasible model for object recognition, based on how the visual cortex processes information. However, computational cost is the biggest obstacle of this model. This paper aims...
In this work, we present a comparative evaluation of various ‘tracking-by-detection’ approaches on public datasets. The work investigates popular sequential Monte Carlo and template ensemble based trackers coupled with relevant visual people detectors with emphasis on exhibited performance variation depending on tracker-detector choice. Extensive experimental results are provided on public dataset...
We present a new approach for feature pooling in human action recognition. Instead of partitioning videos at predefined uniform intervals in a spatial-temporal volume as done with spatial pyramid matching, our method adaptively partitions in a pooling attribute space, defined by multiple trajectory-based cues. The pooling attributes include individual spatial and temporal coordinates of a trajectory,...
Feature selection for clustering is a challenging problem due to the absence of class labels. Existing approaches can select a feature subset to maintain clustering performance while reducing dimensionality. However, we are faced with two problems: (1) there could be many sets of features that seem equally good, and (2) these features are sensitive to small data perturbation, or the selection instability...
Frog protection has become increasingly essential due to the rapid decline of its biodiversity. Therefore, it is valuable to develop new methods for studying this biodiversity. In this paper, a novel feature extraction method is proposed based on perceptual wavelet packet decomposition for classifying frog calls in noisy environments. Pre-processing and syllable segmentation are first applied to the...
Detection, classification, and tracking of people and vehicles are fundamental processes in intelligent surveillance systems. The use of publicly available data set is the appropriate way to compare the relative merits of existing methods and to develop and assess new robust solutions. In this paper, we focus on the maritime domain and we describe the generation of boat classification data sets, containing...
With the explosive increase of data volume, the research of data quality and data usability draws extensive attention. In this work, we focus on one aspect of data usability -- incomplete data imputation, and present a novel missing value imputation method using stacked auto-encoder and incremental clustering (SAICI). Specifically, SAICI's functionality rests on four pillars: (i) a distinctive value...
Keystroke dynamics authentication is not as widely used compared to other biometric systems. In recent years, keystroke dynamic authentication systems have gained interest because of low cost and integration with existing security systems. Many different methods have been proposed for data collection, feature representation, classification, and performance evaluation. The work presents a detailed...
It is important for network operators to know how users use the network to plan and design network facilities. In this paper, we propose flow classification method using binned time-series data in consideration of practicality. In this paper, we evaluate the proposed method by using mobile data traffic and show the method can maintain classification accuracy as compared with method using the whole...
Human-action recognition through local spatio-temporal features have been widely applied because of their simplicity and its reasonable computational complexity. The most common method to represent such features is the well-known Bag-of-Words approach, which turns a Multiple-Instance Learning problem into a supervised learning one, which can be addressed by a standard classifier. In this paper, a...
Sentiment analysis deals with identifying polarity orientation embedded in users' comments and reviews. It aims at discriminating positive reviews from negative ones. Sentiment is related to culture and language morphology. In this paper, we investigate the effects of language morphology on sentiment analysis in reviews written in the Arabic language. In particular, we investigate, in details, how...
Electrocardiograms (ECG) emerged as a novel biometric identification system in the past decade which yields high level of uniqueness and permanence. Moreover ECG provides inherent characteristic of liveness of a person, so it can furnish a superior solution as compared to other biometric techniques. This research provides with the complete systematic approach for ECG based person identification in...
The performance of network intrusion detection systems based on machine learning techniques largely depends on the selected features. However, choosing the optimal subset of features from a given feature set requires extensive computing resources. To tackle this problem we propose an optimal feature selection algorithm based on a local search algorithm. In order to evaluate the performance of our...
In this paper, a global algorithm for human action, facial and gesture recognition is presented. The proposed algorithm depends on the extraction of multiple transform domain features and Canonical Correlation Analysis (CCA) for features fusion and classification. The proposed algorithm achieved the best reported results for facial and facial expression recognition. Excellent comparable results were...
Drug trafficking organizations are using “go-fast” boats, small fishing boats and commercial containers to smuggle illegal drugs. Because that, detection, classification, and tracking of small vessels are important tasks for improving the security of complex maritime systems. This paper presents a simple method based on the least square method, averaging operator, instead of T-norm operator, and triangular...
In this paper, a Binary Robust Invariant Scalable Keypoints (BRISK) based detection is utilized to facilitate the flying unmanned aerial vehicle (UAV) localization within its autonomous landing on the runway. Specifically, two target detection algorithms are proposed and developed as the BRISK-supported approach. Dataset of images and differential GPS are recorded by a ground stereo vision guidance...
this paper presents a new approach to extract image features for texture classification. The extracted features are obtained by a dominant-completed modeling of the traditional local binary pattern (LBP) operator, which is robust to image rotation, grey scale changing and insensitive to noise and histogram equalization. The main idea of this texture classification approach is that a dominant center...
The fast growing use of social networking sites among the teens have made them vulnerable to get exposed to bullying. Cyberbullying is the use of computers and mobiles for bullying activities. Comments containing abusive words effect psychology of teens and demoralizes them. In this paper we have devised methods to detect cyberbullying using supervised learning techniques. We present two new hypotheses...
Stereo-footprint is a vital trace evidence of criminal detection. Thus, it is important to make a high accuracy feature extraction of the stereo-footprint. In this paper, a system of stereo-footprint data acquisition-recognition is designed. In the system, feature extraction is completed through CP35MHT80 which offered by Wenglor, image extraction is gotten through C920 which is offered by Logitech...
With the development of computer vision technology, many researches about feature detectors and descriptors have been published in the last decades. In order to explore what kind of approaches are appropriate for unmanned aerial vehicle (UAV) onboard video processing, the popular feature detectors and descriptors are analyzed and combined with each other. Three practical videos captured in indoor...
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