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The pollen grains of different plant taxa exhibit various shapes and sizes. This structural diversity has made the identification and classification of pollen grains an important tool in many fields. Despite the myriad of applications, the classification of pollen grains is still a tedious and time-consuming process that must be performed by highly skilled specialists. In this paper, we propose an...
The usage of non-scripted lecture videos as a part of learning material is becoming an everyday activity in most of higher education institutions due to the growing interest in flexible and blended education. Generally these videos are delivered as part of Learning Objects (LO) through various Learning Management Systems (LMS). Currently creating these video learning objects (VLO) is a cumbersome...
This paper proposes a markerless video analytic system for quantifying body parts movement while lying. These movements include: hand, leg, both hand & leg and turning to left or right movements. Combination of pixel intensity and area difference of both segmented and the whole parts of each silhouette compared with the following silhouettes would provide a useful cue for detection of different...
The human experience in the analysis of the handwriting of male and female writers indicates that gender affects the appearance of the handwritten text. These differences are usually very difficult to describe numerically. In order to analyze the handwriting differences between male and female writers, several shape description techniques, such as the tangent angle function, curvature function and...
Facial asymmetry is an important characteristic used in a number of applications. It plays a vital role in human perception of attractiveness and as such has been used in psychology including research on facial expressions evaluation as well as in plastic surgery and orthodontics. It has been also recognized as a biometric feature used for identification and has important applications in detection...
Since depth measuring devices for real-world scenarios became available in the recent past, the use of 3d data now comes more in focus of human action recognition. Due to the increased amount of data it seems to be advisable to model the trajectory of every landmark in the context of all other landmarks which is commonly done by dimensionality reduction techniques like PCA. In this paper we present...
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...
Human detection is one of the hard problems in object detection field. There are many challenges like variation in human pose, different clothes, non-uniform illumination, cluttered background and occlusion which make this problem much harder than other object detection problems. Defining good features, which can be robust to this wide range of variations, is still an open issue in this field. To...
Video surveillance is an active research topic in computer vision. Recent research in video surveillance system has shown an increasing focus on creating reliable systems utilizing non-computationally expensive technique for detecting and observing humans' appearance, movements and activities. In this paper, we present a human identification technique suitable for video surveillance. The technique...
Pedestrian detection is of much importance for its practical applications. This paper develops a novel pedestrian detection system which consists of three stages: motion region detection based on background modeling, feature extraction in the guidance of prior information, and map-based classification applying support vector machine (SVM) and Adaboost. First of all, an adaptive Gaussian Mixture Model...
Falls are a major threat to the independence and quality of life of elderly people. As the worldwide population of elderly increases each year, responding to falls is essential. Computer vision systems provide a new promising solution in responding falls through detecting fall events. This paper presents a new technique in detecting falls based on human shape variation. The proposed visual based fall...
Pedestrian detection from images is an important and yet challenging task. The conventional methods usually identify human figures using image features inside the local regions. In this paper we present that, besides the local features, context cues in the neighborhood provide important constraints that are not yet well utilized. We propose a framework to incorporate the context constraints for detection...
Human age estimation based on face images can figure in a wide variety of real-world applications. In this paper, we propose a novel and efficient facial age estimation algorithm which decides human age in a hierarchical framework. Biologically, human lives can be roughly divided into two stages, the period from birth to adulthood and the period from adulthood to old age, which are quite different...
Swift lets are birds contained within the four genera Aerodramus, Hydrochous, Schoutedenapus and Collocalia. To date, the bird nest grading is based on weight, shape and size. The inspection and grading for raw edible bird nest were performed visually by expert panels. This conventional method is relying more on human judgments. A Fourier-based shape separation (FD) method was developed from Charge...
In gait recognition field, template-based approaches such as Gait Energy Image (GEI) and Chrono-Gait Image (CGI) can achieve good recognition performance with low computational cost. Meanwhile, CGI can preserve temporal information better than GEI. However, they pay less attention to the local shape features. To preserve temporal information and generate more abundant local shape features, we generate...
Despite their high stability and compactness, affine moment invariants have received a relatively little attention in action recognition literature. In this paper, we introduce an approach for activity recognition, based on affine moment invariants. In the proposed approach, a compact computationally-efficient shape descriptor is developed by using affine moment invariants. Affine moment invariants...
The objective of this paper is to study the performance of human reidentification based on multi-shot SURF and to assess its degradation according to the angular difference between the test and reference video scene view angles. In this context, we propose a new automatic statistical method of acceptance and rejection of SURF correspondence based on the likelihood ratio of two GMMs learned on the...
In this paper, we present a novel method for gait recognition of different people groups based on Fourier descriptors (FDs) and support vector machine (SVM). The proposed method involves the procedures of background modeling, extraction of gait silhouettes by background subtraction, shadow removal, representation of gait silhouettes using the FDs, and recognition of human gaits by an SVM Classifier...
Posture language is rich in ways for individuals to express a variety of desire, feelings and thoughts. Recognizing human posture via computer is a challenging task as it involved multiple issues ranging from image, recognition algorithm and system resources. This proposed work aimed to solve viewpoint variation issue through causal topology design Hidden Markov Model (HMM) for view independent multiple...
In this paper, we present a simple yet effective approach to recognizing human activities from video sequences. Our approach integrates the advantages of human action recognition in static images using action key poses and motion based approaches using the variants of Motion History Images (MHI) and Motion Energy Images(MEI). We combine both methodologies to extract a new representation of temporal...
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