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In this paper, we propose a crowd density estimation algorithm based on multi-class Adaboost using spectral texture features. Conventional methods based on self-organizing maps have shown unsatisfactory performance in practical scenarios, and in particular, they have exhibited abrupt degradation in performance under special conditions of crowd densities. In order to address these problems, we have...
Biometric recognition based on the characteristics of human faces has attracted a great deal of attention over the past few years. However, the similarity in the facial appearance of identical twins has made the task difficult and has even compromised commercial face recognition systems. In this paper, we shed new light on the study of facial recognition of identical twins and propose a novel approach...
This research work proposes an innovative processing scheme for the exploitation of eye movement dynamics on the field of biometrical identification. As the mechanisms that derive eye movements highly depend on each person's idiosyncrasies, cues that reflect at a certain extent individual characteristics may be captured and subsequently deployed for the implementation of a robust identification system...
Most of current 3D face reconstruction methods based on 2D image are complex. In this paper, a novel and efficient method on the basis of geometric transformation is presented. The method is composed of two aspects, pose estimation and 3D model reconstruction. For the first part, an improved Active Shape Model(ASM) algorithm is used to detect the feature points of the face in the image, and the frontal...
This paper presents the use of design grammars to evolve playable 2D platform levels through grammatical evolution (GE). Representing levels using design grammars allows simple encoding of important level design constraints, and allows remarkably compact descriptions of large spaces of levels. The expressive range of the GE-based level generator is analyzed and quantitatively compared to other feature-based...
In managing multimedia services, it is important to understand how network performance affects user experience. The model presented in this paper aims to estimate user perception of video quality based on defect events, which are automatically classified by machine learning techniques. The underlying principle of our model is that human experience is event-based and there is a strong correlation between...
In this paper, we describe Object Pixel Mixture Classifiers (OPMCs) which classify an object not only apart from background but also from other objects based on Gaussian Mixture Model (GMM) classification. The proposed OPMC is different from general GMM based classifiers in the respect that novel pairwise threshold is applied for final classification. Pairwise thresholds are different thresholds depending...
This paper presents an ultrasonic sensing based human face identification approach. As a biometric identification method, ultrasonic sensing could detect the geometric structure of faces without being affected by the illumination of the environment. Multi ultrasonic sensors are used for data collection. Continuous Transmitted Frequency Modulated (CTFM) signal is chosen as the detection signal. High...
Detection and classification of significant human motions are important tasks when analyzing a video that records human activities. Among various human motions, we consider that repetitious motions are specially important since they are usually results of activities with clear intentions. In this paper, we propose and evaluate a method that detects video segments that contain repetitious motions,...
Human tracking is an important vision task in video surveillance and perceptual human-computer interfaces. This paper presents a novel algorithm for region-based human tracking using color and depth features. We propose an adaptive autoregressive logarithmic search (ARLS) to estimate the target position, and use depth information to further reduce the false alarm rate. The new ARLS algorithm is evaluated...
The efficient browsing and retrieval of videos is a fundamental part of current multimedia systems especially on mobile devices. One way to provide enjoyable video browsing to the users is by providing summaries of the videos whereby the users can have a clue of the contents of the video before watching the video itself. In this paper, we propose a key frame extraction based video summarization technique...
The bag-of-words approach with local spatio-temporal features have become a popular video representation for action recognition. Recent methods have typically focused on capturing global and local statistics of features. However, existing approaches ignore relations between the features, particularly space-time arrangement of features, and thus may not be discriminative enough. Therefore, we propose...
Pedestrian detection is an important part of intelligent transportation systems. In the literature, Histogram of Oriented Gradients (HOG) detector for pedestrian detection is known for its good performance, but there are still some false detections appearing in the cases with flat area or clustered background. To deal with these problems, in this research work we develop a new feature which is based...
A new retrieval technique of salient image features is proposed in this research and this technique firstly detects the feature points by using Harris corner detector to find out the feature region of image. And then compute the mean of color, variance, the number of occurrence of color and color aggregation and any eigenvector in accordance with the chrominance and lightness of feature region to...
In recent years, a large amount of research efforts have been spent in the tracking human targets using one or more visual sensors (cameras) in both indoor and outdoor security and surveillance environments such as airports, metro stations, etc. However, in majority, the problem of associating a reliable identification signature to a detected target when in motion, has often been complicated due to...
Pedestrian detection is a major difficulty in the field of object detection. In order to achieve a balance between speed and accuracy, we propose a new framework in pedestrian detection based on HOG-PCA and Gentle AdaBoost. Firstly, each block-based feature of the image is encoded using the histograms of oriented gradients (HOG), then Principal Components Analysis (PCA) is used to reduce the dimensions...
A story is defined as "an actor(s) taking action(s) that culminates in a resolution(s)." In this paper, we investigate the utility of standard keyword based features, statistical features based on shallow-parsing (such as density of POS tags and named entities), and a new set of semantic features to develop a story classifier. This classifier is trained to identify a paragraph as a "story,"...
Text Summarization is the process of identifying and extracting the most vital information in a document. It has been seen as an effective method for dealing with increasing amount of information on the Internet nowadays. In this paper, we present an application of Genetic Programming to the problem of Automatic Text Summarization. Genetic Programming was used to evolve the function that ranks the...
This paper presents a novel approach called PEPA (Perceptual Edges Preservation Algorithm) which enables computing machines to mimic the human vision capability in perceiving meaningful objects in an input scene, characterized in that the preserved edges are conformal to human vision perception. The approach mainly comprises three stages: (1) applying linear and nonlinear filtering to mimic the capability...
Human gait is the main activity of daily life. Gait can be used for applications like human identification (in medical field etc). Since gait can be perceived from a distance it can be used for human identification. Gait recognition means identifying the person with his/her gait. Human identification using gait can be used in surveillance. A method is proposed for gait recognition using a technique...
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