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Image processing is a method of extracting some useful information by converting image into digital inform by performing some operations on it. Object detection and tracking are the task that is important and challenging such as video surveillance and vehicle navigation. Video surveillance is a technology which works in dynamic environment in various events such as sports, public safety, and management...
Video surveillance system is widely adopted in order to secure life. This paper presents embedded home surveillance systems to detect intruder in home environment. Proposed system works on embedded Linux board which is equipped with an ordinary web camera. At software level, it uses Open Computer Vision library to detect intruder in two different steps, Histogram of Oriented Gradient and Haar Like...
This paper presents a study on a family of local hexagonal and multi-scale operators useful for texture analysis. The hexagonal grid shows an attractive rotation symmetry with uniform neighbour distances. The operator depicts a closed connected curve (1D periodic). It is resized within a scale interval during the conversion from the original square grid to the virtual hexagonal grid. Complementary...
Graph kernels are powerful tools for structural analysis in computer vision. Unfortunately, most existing state-of-the-art graph kernels ignore the locational or structural correspondence information between graphs, based on the visual background. This drawback influences the performance of existing kernels for computer vision based classification problems, e.g., classification of shapes, point clouds...
Colour, texture, shape, and relative position descriptors are fundamental visual descriptors. In particular, a relative position descriptor is a quantitative representation of the relative position of two spatial objects, and a basis from which models of spatial relationships (like inside, above, around, near) can be derived. The affine properties of visual descriptors have been the subject of much...
Shape-based registration methods frequently encounters in the domains of computer vision, image processing and medical imaging. The registration problem is to find an optimal transformation/mapping between sets of rigid or non-rigid objects and to automatically solve for correspondences. In this paper we present a comparison of two different probabilistic methods, the entropy and the growing neural...
Affine invariant point-set matching is an important issue in computer vision and pattern recognition. Using reference points derived from the convex hull of the point-set is an existing idea to solve this problem. However, how to choose proper and enough reference points for extracting affine invariant and powerful discriminative descriptors is an open problem. In this paper, a novel method termed...
In this paper, we present the first multi-body non-rigid structure-from-motion (SFM) method, which simultaneously reconstructs and segments multiple objects that are undergoing non-rigid deformation over time. Under our formulation, 3D trajectories for each non-rigid object can be well approximated with a sparse affine combination of other 3D trajectories from the same object. The resultant optimization...
In recent years, hand gesture recognition framework as an effective sign language tool has been extensively explored by many researchers. This paper presents an idea of developing a framework using computer vision for hand gesture based sign language recognition from real-time video stream. The proposed system identifies hand-palm in video stream based on skin color and background subtraction scheme...
Hand shape classification is an important problem for the human computer interaction and the finger-spelling recognition. For this matter, what is needed is a real-time processing and scale invariance. To this end, we propose a feature vector for hand shape classification, which is fast, and robust to scale. The proposed method calculates an adaptive k-curvature which computes a curvature depending...
With the purpose of achieving automated detection of crowd abnormal behavior in public, this paper discusses the category of typical crowd and individual behaviors and their patterns. Popular image features for abnormal behavior detection are also introduced, including global flow based features such as optical flow, and local spatio-temporal based features such as Spatio-temporal Volume (STV). After...
Over the last few years, the use of medium density fibreboard (MDF), oriented strand board (OSB) and other particleboard (grade B wood) has increased dramatically in the timber industry. This represents a major challenge for the wood recycling industry, which grinds this wood into chips to sell it to the wood chip industry. For this reason, the demand for an accurate, reliable, cheap and fast system...
Quality of food and agricultural products is vital for farmers and consumers. Quality based classification of these products is being carried out manually in the industry which is tedious and expensive. Computer Vision systems can be used to automate the classification process. Automation can reduce the production cost and improve the overall quality. A computer vision system captures the image of...
The objective of extended object tracking is to simultaneously track a target object and estimate its shape. As a consequence, it becomes necessary to incorporate both location and shape errors in the performance assessment of extended object tracking methods. In this work, we highlight the difficulties of selecting a proper metric for this purpose and discuss currently used metrics from literature...
In this paper we present a method to recover the shading and specularities in the scene from a single image. The method presented here is based on the dichromatic model and enforces a local smoothness assumption over the object surfaces in the scene. This naturally leads to a setting where the estimate of the shading at a particular pixel can be expressed in terms of its neighbours up to a pair of...
Photometric ambient occlusion estimation is to recover the local visibility of a scene from multiple illuminations at a fixed viewpoint. Its effectiveness is highly dependent on the amount of illuminations. In this paper, we study how to reliably extract photometric ambient occlusion from sparsely sampled illuminations. We specifically propose an effective relative entropy minimization framework to...
Moving object localization is a popular study in contemporary computer vision, provided the fact that many challenging problems, such as illumination changes, obstacles, object shape transformation, etc, are still to be deeply investigated and properly tackled in moving object localization for the time being. In this study, a new clustering-based strategy is introduced to realize the moving object...
Researchers gave the vehicle and pedestrian detection lots of attention to alarm the drivers for improving the safety of transportation systems. However, bicycles are also the significant factor of the safety on road. In this paper, a bicycle detector for side-view image is proposed based on the observation that a bicycle consists of two wheels in the form of ellipse shapes and a frame in the form...
It is an important task to count the number of the objects in the image automatically. Because the objects in the image are sometimes overlapped with each other and even covered with different shaped objects, it is very difficult to detach these objects before counting them. Circular Hough transform has been used extensively to detect and count overlapped objects with circular shapes. However it can...
Event-based temporal contrast vision sensors such as the Dynamic Vison Sensor (DVS) have advantages such as high dynamic range, low latency, and low power consumption. Instead of frames, these sensors produce a stream of events that encode discrete amounts of temporal contrast. Surfaces and objects with sufficient spatial contrast trigger events if they are moving relative to the sensor, which thus...
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