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In this paper we propose a probabilistic model to parameterize human interactive behaviour from human motion. To Support the model taxonomy, we use Laban Movement Analysis (LMA), proposed by Rudolph Laban [11], to characterize human non-verbal communication. In interpersonal communication, body motion carries a lot of meaningful information, useful to analyse group dynamic behaviors in a wide range...
In this paper, we present a novel approach for human action recognition with histograms of 3D joint locations (HOJ3D) as a compact representation of postures. We extract the 3D skeletal joint locations from Kinect depth maps using Shotton et al.'s method [6]. The HOJ3D computed from the action depth sequences are reprojected using LDA and then clustered into k posture visual words, which represent...
Our primary motivation in this paper is to determine whether evolved texture feature extraction programs are competitive with human derived programs for a difficult real world texture classification problem. The problem involves distinguishing images of three classes of bulk malt. There are subtle differences between the three classes. We have used a number of human derived methods, Haralick, Gabor,...
We propose an unsupervised image segmentation method based on texton similarity and mode seeking. The input image is first convolved with a filter-bank, followed by soft clustering on its filter response to generate textons. The input image is then superpixelized where each belonging pixel is regarded as a voter and a soft voting histogram is constructed for each superpixel by averaging its voters'...
While the detection of the interesting regions in images has been extensively studied, relatively few papers have addressed surfaces. This paper proposes an algorithm for detecting the regions of interest of surfaces. It looks for regions that are distinct both locally and globally and accounts for the distance to the foci of attention. Many applications can utilize these regions. In this paper we...
In many visual classification tasks the spatial distribution of discriminative information is (i) non uniform e.g. person ‘reading’ can be distinguished from ‘taking a photo’ based on the area around the arms i.e. ignoring the legs and (ii) has intra class variations e.g. different readers may hold the books differently. Motivated by these observations, we propose to learn the discriminative spatial...
Depth ordering is instrumental for understanding the 3D geometry of an image. Humans are surprisingly good at depth ordering even with abstract 2D line drawings. In this paper we propose a learning-based framework for depth ordering inference. Boundary and junction characteristics are important clues for this task, and we have developed new features based on these attributes. Although each feature...
We present an approach to automatically learn the visual appearance of an environment in terms of object classes. The procedure is totally unsupervised, incremental, and can be executed in real time. The traversability property of an unseen object is also learnt without human supervision by the interaction between the robot and the environment. An incremental version of affinity propagation, a state-of-the-art...
It is crucial to get human hand information for hand gesture recognition tasks. However, at present, people can not still get a perfect hand segmentation or localize hand accurately especially under complex conditions. Therefore, it is necessary to develop robust and effective methods for detecting human hand accurately. In this paper, we propose a new method for hand detection. We present an extended...
In this paper we propose a local space-time descriptor to be employed for behaviour analysis in video-surveillance applications. We show how this local video representation is able to extract scene semantics in both a supervised (behaviour recognition) and semi-supervised (anomaly detection) setup. Our approach yields state-of-the art performance on two publicly available datasets and is not computationally...
Exchange of medical information between hospitals is an essential part for medical treatments. In addition, security issues relating to electronic exchanges of information should also be concerned to protect the patient's privacy and to help the treatments. In cooperation with the Health Level seven (HL7) standard, we employ reversible data hiding to further assist reducing the human errors during...
Gender and ethnicity classification are challenging topics in the field of face analysis. Some features, like skin color, are relevant only for ethnicity but not for gender; some others, like face geometry, are important for both. The impact of ethnicity in gender perception, as the effect of gender on ethnicity disambiguation, is not clear. This paper provides a study to check if gender and ethnicity...
The Agricultural industry on the whole is ancient so far. Quality assessment of grains is a very big challenge since time immemorial. The paper presents a solution for quality evaluation and grading of Rice industry using computer vision and image processing. In this paper basic problem of rice industry for quality assessment is defined which is traditionally done manually by human inspector. Machine...
Increased frequency of micronuclei is positively correlated with the molecular dosimetry of genotoxic damages. The cytokinesis-block micronucleus test (CBMN test) is a well-established assay used in toxicological screening for potential genotoxic compounds. Since the method is simple and economical, CBMN assay can be employed on a large scale as a quantitative biological dosimeter. Automated detection...
Human action recognition and interpretation constitutes an important part of the video understanding. In this work, a novel action recognition system is developed that uses edge features obtained from optical flow power shapes which is represented as sequential gradient histograms. The presented system can achieve equal results to the complicated top action recognition systems of nowadays. The system...
This paper proposes an occlusion resistant automatic fall detection framework for smart environments. There are two major contributions of the proposed method. First, synchronized RGB and depth data are utilized together to capture both apperance and geometrical characteristics of human silhouettes in the environment. Second, unlike existing methods, a single Kinect sensor is mounted on a ceiling...
Color image segmentation is a critical pre-process in image processing. Also it's important in the field of computer vision and pattern recognition. In this paper, we first state some evidence in the human vision research. Not all the intensity from 0 to 255 in RGB spaces can be distinguished by human vision. So we reduce the level of the intensity in RGB space to 26,28,26 respectively, while maintaining...
An innovative way of object shape representation using Density Histogram of Feature Points (DHFP) is introduced and used in this paper. We have named this method Enhanced Density Histogram of Feature Points (EDHFP). We use silhouette images where the image region ξ consists of only those pixels that correspond to points on the object and have a value one (1) indicating “on” pixels. We count the number...
Traffic accidents are decreasing under the influence of technology advancement. But the problems still remain that accidents occur due to carelessness of drivers. Therefore many researchers have been still studying to realize an advanced safety system. The Histograms of Oriented Gradients (HOG) feature is well known as a useful method of detecting a standing human in various kinds of the background...
This paper presents an efficient algorithm to set adaptive ROI for detecting pedestrians in a moving vehicle environment. The algorithm analyzes the centroid of detected pedestrian in current frame and define centroid region where centroids of detected pedestrian are concentrated. Based on centroid region, adaptive ROI is updated for each different size of detection window in next frame. Experiments...
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