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In this paper, an integrated video surveillance system for robust tracking is introduced. In the blob detection part, an optical flow algorithm for crowded environment is studied experimentally and a comparison study with respect to traditional subtraction approach is carried out. In the segmentation part, different algorithms are fused to develop a hybrid algorithm for stable segmentation, and validation...
In this paper, we propose a system to extract the moving object by the segmentation based on fast optical flow estimation. This optical flow estimation is based on multichannel integration for speeding up and can estimate more accurate optical flow fast. Moving object can be extracted by the segmentation using the obtained optical flow. Experimental results show that the segmentation based on the...
In this paper we propose an optical flow estimation method based on compensating method by using spatiotemporal differentiation. Technique using spatiotemporal differentiation is one of optical flow calculation method. This method enables us to calculate velocity distribution rapidly, but the error in the approximation of derivative coefficients increases as the displacement of the moving pattern...
Optical flow is a research topic of interest for many years. It has, until recently, been largely inapplicable to real-time applications due to its computationally expensive nature. This paper presents a new reliable flow technique which is combined with a motion detection algorithm, from stationary camera image streams, to allow flow-based analyses of moving entities, such as rigidity, in real-time...
This paper is dedicated to detecting and counting vehicles in day environment by using real time traffic flux through differential techniques. The basic idea used is variation in the traffic flux density due to presence of vehicle in the scene. In the present work a simple differential algorithm is designed and tested with vehicle detection and counting application. Traffic flux estimation will play...
Real time dynamic scene analysis has become very important aspect as the increase in video input analysis. Although several dynamic scene analysis techniques are available, some of them poses increased computational complexity problem. In the present work a simple differential algorithm is designed and tested with traffic flux estimation application. Traffic flux estimation will play a very vital...
This paper presents an object tracking system that utilises a hybrid multi-layer motion segmentation and optical flow algorithm. While many tracking systems seek to combine multiple modalities such as motion and depth or multiple inputs within a fusion system to improve tracking robustness, current systems have avoided the combination of motion and optical flow. This combination allows the use of...
The basic idea of Lucas and Kanade is to constrain the local motion measurement by assuming a constant velocity within a spatial neighborhood. We reformulate this spatial constraint in a probabilistic way assuming Gaussian distributed uncertainty in spatial identification of velocity measurements and extend this idea to scale and time dimensions. Thus, we are able to combine uncertain velocity measurements...
Graph-cut methods have become an intensive area of research in image processing, with applications to stereo vision, binary thresholding, classification and image de-noising amongst other areas. This paper describes novel graph-cut implementations for use in two applications: 2D optical flow and interactive object delineation. The optical flow implementation is based on recursive application of graph-cuts,...
Cylindrical panoramic mosaics can be created by aligning and stitching images from a series, captured by a camera rotating around its optical center. The transformation between two images must then be found. Existing methods compute a global transformation for the whole image starting from pixels in the overlapping region. This global transformation, due to local distortions often results in ghost...
Longitudinal motion artifacts in intravascular ultrasound (IVUS) sequences hinders a properly 3D reconstruction and vessel measurements. Most of current techniques base on the ECG signal to obtain a gated pullback without the longitudinal artifact by using a specific hardware or the ECG signal itself. The potential of IVUS images processing for phase retrieval still remains little explored. In this...
This paper describes an approach to optical flow computation that combines local and global constraints. A local flow estimate is obtained at each pixel, and is used to segment the image into regions of smooth motion. Within each region, global constraints are applied to reduce noise in local flow estimates while preserving motion boundaries. The main novel contributions in this framework are: (1)...
Variational techniques yield the most accurate results for dense optical flow fields between two images. They have the nice property of inherent smoothness to cope with untextured image regions: the filling-in of such regions is driven by neighbouring pixels. Such filling-in is not always the best choice. If the scene is mostly stationary and the camera is moving, the direction of the optical flow...
A means has been developed of deriving range images from sequences of conventional images taken by a single passive camera (forward looking or side looking) on-board a vehicle as it moves continuously relative to the scene. These range images can provide the 3D situational awareness needed for autonomous operation of the vehicle. The first image in a sequence is registered in turn with each subsequent...
This paper characterizes the bias of a gradient-based shift estimator (GBSE) and proposes a novel scheme to correct for the bias. The bias of GBSE comes from an inaccurate estimate of the image gradient energy, which is due to noise, aliasing and built-in low-pass filtering. For subpixel shift, the bias is linearly proportional to the true shift. The linear bias factor can be blindly estimated using...
Reliable segmentation and motion tracking algorithms are required to achieve gesture detection and tracking for human-machine interaction. In this paper we present an efficient method for detecting and tracking moving hands in sign language video frames. We make use of the geodesic active region framework in conjunction with new color and motion forces; color information is provided by a skin color...
Optical flow forms an important initial processing stage for many machine vision tasks. A framework is presented for the recovery of dense optical flows from image sequences containing large motions. Sparse feature correspondences are used to assign multiple optical flow hypotheses to each image pixel which are then independently refined to produce a further set of refined hypotheses. One final flow...
Background subtraction is an essential element in most object tracking and video surveillance systems. The success of this low-level processing step is highly dependent on the quality of the background model maintained. Gutchess et al. [4] proposed a novel background initialization algorithm that utilizes local optical flow information to locate the stable interval (of intensity values) which is most...
This article presents a simple method on how to implement a super-resolution based video enhancement technique in .NET using the functions of the OpenCV library. First, we outline the goal of this project and after that, a short review of the steps of super-resolution technique is given. As a part of the discussion about the concrete implementation, firstly the general design aspects are detailed...
This paper presents a new approach to estimate the optical flow problem. Many estimation methods have been proposed, but instabilities at boundaries of moving objects still presents a challenge in assessing optical flow. In this approach, we propose a new algorithm which is used to detect and readjust quickly unstable regions in result of estimating optical flow. Besides, we propose an anisotropic...
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