The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Voice spam is a major serious issue that would lead the people's lives a few inconveniences in recent years. In this paper, a model based on user behavior pattern is proposed to design an anti spam calls technique. The basic idea for the technique is that spammers with revenue motivation behave significantly distinct to legitimate callers. The characteristic parameters representing user behavior pattern...
We propose a method of clustering images that combines algorithmic and human input. An algorithm provides us with pairwise image similarities. We then actively obtain selected, more accurate pairwise similarities from humans. A novel method is developed to choose the most useful pairs to show a person, obtaining constraints that improve clustering. In a clustering assignment elements in each data...
This paper demonstrates an implementation of pool-based active learning through uncertainty sampling using a Variational Dirichlet Process (VDP) model. The VDP is used for both pre-clustering and classification, and is extended to incorporate fixed labels from an oracle (human annotator). Three different uncertainty sampling techniques are explored - least confident sampling, margin sampling and entropy...
Human activity classification has wide-spread applications ranging from human computer interaction to disease progression studies. In this paper we propose a body posture model based on the Euler angles of the torso, arms and legs. The Euler angles are computed based on data streams originating from a wireless Body Sensor Network (BSN) comprising of nine accelerometers. Thereafter they are used to...
This paper introduces the clustering-based sentiment analysis approach which is a new approach to sentiment analysis. By applying a TF-IDF weighting method, voting mechanism and importing term scores, an acceptable and stable clustering result can be obtained. It has competitive advantages over the two existing kinds of approaches: symbolic techniques and supervised learning methods. It is a well...
Behavior recognition is an attractive direction in the computer vision domain. In this paper, we propose a novel behavior recognition method based on prototype learning using metric learning. Prototype learning algorithm can improve the classification performance of nearest-neighbor classifier, reduce the storage and computation requirements. And the metric learning algorithm is used to advance the...
In this paper, the AFS fuzzy logic clustering algorithm proposed by X.D. Liu has been studied further by the improvement of the algorithm. Instead of examples of less than 10 samples in Liu's paper, we apply the improved algorithm to Wisconsin breast cancer data which has 699 samples and just the order relationships of the samples on each feature are used in the algorithm. This study shows that the...
A common approach to human action recognition is to use 2-D silhouettes in the space-time volume as a basis for further extraction of useful features. In this paper, we present a novel motion representation based on difference images. We show that this representation exploits the dynamics of motion, and show its effectiveness in action recognition. Moreover, experimental results demonstrate that this...
In this paper, we present a method that recognizes single or multiple common actions between a pair of video sequences. We establish an energy function that evaluates geometric and photometric consistency, and solve the action recognition problem by optimizing the energy function. The proposed stochastic inference algorithm based on the Monte Carlo method explores the video pair from the local spatio-temporal...
This paper addresses the problem of automatic temporal annotation of realistic human actions in video using minimal manual supervision. To this end we consider two associated problems: (a) weakly-supervised learning of action models from readily available annotations, and (b) temporal localization of human actions in test videos. To avoid the prohibitive cost of manual annotation for training, we...
In the framework of AFS (Axiomatic Fuzzy Sets) theory, We propose A novel weight fuzzy clustering algorithm, which is totally different from the traditional clustering algorithm based approaches. The novel weighted fuzzy clustering algorithm has three main advantages: Firstly, the procedures of the proposed algorithm are more transparent and understandable, and the clustering results not only have...
This paper proposes a novel algorithm for categorization of action video sequences using unsupervised dual clustering. Given a video database, we extract motion information of actions and perform nonlinear dimensionality reduction for addressing both the high dimensionality of silhouette features and non-linearity of articulated human actions. A k-means clustering is first performed on frame-wise...
This paper extends the voting experts (VE) algorithm for unsupervised segmentation of sequences to create the hierarchical voting experts (HVE) algorithm for unsupervised segmentation of hierarchically structured sequences. The paper evaluates the strengths and weaknesses of the HVE algorithm to identify its proper domain of application. The paper also shows how higher order models of the sequence...
Due to the rapid development of motion capture technology, more and more human motion databases appear. In order to effectively and efficiently manage human motion database, human motion classification is necessary. In this paper, we propose an ensemble based human motion classification approach (EHMCA). Specifically, EHMCA first extracts the descriptors from human motion sequences. Then, singular...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.