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A monitoring scope panorama stitching and fast automatic positioning system based on spherical cameras is presented in this paper. Compared to the traditional manual camera control for specified scene monitoring in large surveillance range, the developed system provides a fast and efficient way of automatic adjusting the cameras. A fast stitching approach is deployed to combine the image set from...
Video summarization usually refers to produce a summary preserving essential content of the original video. Many existing methods have been developed to select representative frames by a dictionary learning model, which have led to a state-of-the-art performance. However, learning dictionary without considering relationship between samples of the original data space would lead to imprecise representation...
In this paper we describe a new dataset, under construction, acquired inside the National Museum of Bargello in Florence. It was recorded with three IP cameras at a resolution of 1280 × 800 pixels and an average framerate of five frames per second. Sequences were recorded following two scenarios. The first scenario consists of visitors watching different artworks (individuals), while the second one...
The paper deals with the design and new solutions of application software with the aim to detect and recognize objects sensed by a camera. Objects of the sensed scene were determined and recognized after previous digital processing of data delivered by the camera. To this end the computer vision learning neural-based methods of feature extraction were used. The proposed application software may be...
This research seeks to improve the outcomes of Eulerian Video Magnification in real life scenarios. We address the core requirement in Eulerian Magnification that the person in the video be completely still. The proposed system pre-processes the video in multiple stages using subject targeting and stabilization. The resulting video is better suited to Eulerian Magnification restrictions. Our method...
Autonomous path-following robots that use vision-based navigation are appealing for a wide variety of tedious and dangerous applications. However, a reliance on matching point-based visual features often renders vision-based navigation unreliable over extended periods of time in unstructured, outdoor environments. Specifically, scene change caused by lighting, weather, and seasonal variation lead...
In computer vision, gradient-based tracking is usually performed from monochromatic inputs. However, few researches consider the influence of the chosen colorto- grayscale conversion technique. This paper evaluates the impact of these conversion algorithms on tracking and homography calculation results, both being fundamental steps of augmented reality applications. Eighteen color-togreyscale algorithms...
The detection of play and break segments in team sports is an essential step towards the automation of live game capture and broadcast. This paper presents a two-stage hierarchical method for play-break detection in non-edited video feeds of sport events. Unlike most existing methods, this algorithm performs action and event recognition on content, and thus does not rely on production cues of broadcast...
Recent development in depth sensors opens up new challenging task in the field of computer vision research areas, including human-computer interaction, computer games and surveillance systems. This paper addresses shape and motion features approach to observe, track and recognize human silhouettes using a sequence of RGB-D images. Under our proposed activity recognition framework, the required procedure...
It is extremely time consuming for researchers looking for particular events of interest to manually search in the video database. Therefore, there is enormous scope in research in the field of automatic extraction of key frames from underwater video sequences. Analysis of underwater video poses many challenges to existing techniques in computer vision including camera movement, turbidity, uneven...
Video has difficulty to maintain consistent intensity and color tone from frame to frame. Particularly, it happens when imaging device such as black box camera has to deal with fast changing illumination environment. However, conventional automatic white balance algorithms cannot handle this good enough to maintain tone consistency, which is observed in most commercial black box products. In this...
Drinking activity recognition is not a well-researched area in the human activity recognition area. In this paper, a novel technique to recognize the hand grasping posture in drinking activities is proposed. The proposed method aims to overcome the accuracy issue of Kinect in detecting the correct hand position during drinking activities and no training is required to recognize the grasping posture...
Major issues faced by camera captured document analysis is to deal with the page curl and perspective distortions. Perspective distortion occurs when the world plane is not parallel to the imaging plane. This causes parallel lines to become non-parallel and the objects which are far away from the camera to seem smaller. Rectification is an unavoidable process on images with perspective distortion...
This paper proposes a novel method for detecting the moving vehicles in dynamic urban traffic scenes using a stereo camera. Relying on the fact that a set of feature points on a rigid 3D scene object are staying in a rigid 3D configuration, we propose to compute the relative motion between the camera and a moving object with an algorithm that follows from the visual odometry based motion estimation...
Human action recognition has been one of the most challenging topics in computer vision during the last decade. This paper presents a novel approach for recognizing view independent human actions based on analysis of Fourier transform and Radon transform of self similarity matrix of features obtained from the action. The proposed feature descriptor is extracted from human point cloud over the time...
3D reconstruction is one of the long lasting research topics in computer vision. It is the task of regenerating a model in three-dimensional (3D) space by images taken from the scene. An image-based method for 3D reconstruction based on intersection of planar visual hulls from projective images taken by multiview videos is proposed. Reconstruction can be performed without any further information related...
Analysing distinct motion patterns that occur during infancy can be a way through early prediction of cerebral palsy. This analysis can only be performed by well-trained expert clinicians, and hence can not be widespread, specially in poor countries. In order to decrease the need for experts, computer-based methods can be applied. If individual motions of different body parts are available, these...
Removal of visually unpleasant motion from videos is an important video enhancement technology. We present a feature-based approach for video stabilization that produces stabilized videos, while preserving the original resolution. To characterize the global/camera motion, SIFT features are extracted and carefully chosen to define the homography of 2D perspective warp between two consecutive frames...
In recent years, unmanned autonomous vehicle navigation technology or UAV research is a hot topic in the field of machine vision, and obstacle detection is the basis of autonomous navigation. In this thesis, the author analyzed the deficiency of stereoscopic vision and classified current monocular obstacle detection algorithms. According to the properties of algorithms, this paper elaborated the function...
In this paper a human action recognition algorithm based on two-view of optical flow in multiple layers per camera employing the transform domain and 2DPCA is presented. This method explores more distinctive features between actions. It is not sensitive to translation, alignment and noise. In addition the use of 2DPCA maintains the spatial relation between pixels and increases the recognition accuracy...
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