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The rapid development of three-dimensional (3D) imaging techniques has significantly increased the demand for high resolution (HR) depth video and images. Significant pixel deficiencies and too much noise can be seen in depth images especially taken from Kinect cameras. For this reason, usability in several computer vision applications is restricted. In the acquisition of HR depth images, in traditional...
Crowd behaviour analysis is a challenging task in computer vision, mainly due to the high complexity of the interactions between groups and individuals. This task is particularly crucial given the magnitude of manual monitoring required for effective crowd management. Within this context, a key challenge is to conceive a highly generic, fine and context-independent characterisation of crowd behaviours...
Learning the dynamics of shape is at the heart of many computer vision problems: object tracking, change detection, longitudinal shape analysis, trajectory classification, etc. In this work we address the problem of statistical inference of diffusion processes of shapes. We formulate a general Itô diffusion on the manifold of deformable landmarks and propose several drift models for the evolution...
Automatic and accurate human upper-body detection and orientation estimation have great practical value in several computer vision applications. Most previous works on human upper-body orientation estimation assume that the human upper-body region is already detected and aligned. However, this is not the case in many real-world scenarios. Additional human detector is essential which is usually much...
For low density crowd, the statistical information of pixels and feature points can reflect the change of crowd density. Therefore, pixels and corners are fused in this paper, then, SVR is used to learn the corresponding relationship between feature and the number of people. While PSO is used to optimize the choice of parameters C and gamma in SVR. The experimental results show that the SVR optimized...
Haze is mainly occurred by atmospheric phenomena. Recently, many researchers in haze removal algorithm area are using single image. At the single image, we can't use depth information. To estimate the thickness of haze without depth information is not easy. As a result, single image haze removal method includes halo effect. In this paper, we propose halo effect suppression for single image haze removal...
The present paper describes a low-cost algorithm for video stabilization. Like other feature based algorithms, it is robust to motion blur, noise and illumination changes. Moreover, maintaining real time processing, it is not negatively affected by moving objects in the scene, works fine even in conditions of low details in the background and it is robust to scene changes.
This paper describes the use of two dimensional (2-D) laser scanner for locating badminton shuttlecock in real playing environment. It proposes a method to predict the end point of shuttlecock trajectory. The system is designed using two 2-D laser scanners to locate shuttlecock in midst of air in its trajectory. It helps to calculate shuttlecock's speed, orientation and hence, to predict an end point...
This paper proposes an Eye Gaze Tracking (EGT) technique using a single eye image that can be easily calibrated and mapped for Human Computer Interaction (HCI). The technique employs both geometric and trigonometric relationships to find a user's Point of Regard, followed by calculating user-dependent variables for final mapping onto a user interface (UI). Experimental results show acceptable accuracy...
In recent years, a tremendous research effort has been made in the area of generic object recognition. However, the most important thing is not the names but functions for robots to comprehend objects. Object functions refer to “the purpose that something has or the job that someone or something does”. Various elements (e.g., the physical information, material, appearance and human interaction) independently...
This paper presents a novel image haze removal approach from single image. In the algorithm, the constant albedo and dark channel prior methods are combined to represent the transmission model of hazed image. And then, the quick shift segmentation approach is introduced to decompose the input image into some gray level consistent areas. Compared with traditional fixed image partition schemes, better...
Human pose estimation in monocular still image is a hotspot and difficult issue in the computer vision field, and it has important applicable to many novel area. However, the detecting rate is still poor due to many factors as variety of pose and clothing, occlusion, clustering background etc. A pose estimation approach combining deformable part model and full body model is presented to solve the...
Tree models for human pose estimation have been prevailed in the last decade, which are effective in human pose estimation. This paper aims to incorporate the appearance symmetry of human limb parts into tree model and address the problem of the wrong detection of human limbs. For a pair of symmetrical limbs, such as for legs and arms, their appearances are similar that can use a distance to represent...
Pedestrian flow estimation is a vital issue in video surveillance. Inspired by fluid mechanics we proposed to model the pedestrian flow as time-dependent fluid, and estimate the pedestrian flow using flux. Firstly, optical flow is used to construct the motion vector field. Then, we compute the inside and outside flux components within fixed areas to estimate the pedestrian flow in different direction...
In crowd surveillance systems, it is important to select the proper analysis algorithm considering the properties of the video content. The inappropriate algorithm selection may result in performance degradation and generation of false alarms. An important feature of crowd videos is the density of the crowd. While object detection and tracking based algorithms are feasible for low density crowds,...
Optical transmission estimation is a key procedure for removing haze from certain outdoor images. In this paper, we propose a novel transmission estimation model called the luminance reference model. A luminance reference, which is the intensity lower bound of a local region in the haze free image, is assumed to be a global constant across the image. Based on this assumption, we theoretically prove...
Stereo matching has a long history in image processing and computer vision. In fact, there are inumerous approaches reported in the literature, and quantitative evaluation is usually performed by comparing the obtained disparity maps with ground truth data (using the MSE, for instance). One important application of stereo matching is view interpolation, where it is desired to produce a new synthetic...
Estimating depth in monoscopic images and videos is a non-trivial problem due to the inherent ambiguity that arises when a 3D scene is projected onto a 2D plane (the image). But because depth estimation is so useful, many different techniques have been developed to solve this problem. Unfortunately these methods tend to be computationally intensive or require precise knowledge about the camera that...
While various privacy protection filters have been proposed in the literature, little importance has been given to the context relevance of these filters. In this paper, we specifically focus on the dependency between privacy preservation and crowd density. We show that information about the crowd density in a scene can be used in order to adjust the level of privacy protection according to the local...
In this paper, we propose a fast and efficient method for estimating a homography. The homography is used to generate a stitched image such as UHD (Ultra-High-Definition) image from multiple HD (High-Definition) images. The homography estimation is the most important part in stitching techniques because the accuracy of the estimated homography means confidence of correspondence between the HD images...
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