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This article develops a geometric framework for detecting targets, in the form of regions of interest, from certain sonar imagery. The main idea is to extract level sets from voxel images and compute local geometric features of the resulting surfaces. Examples include Gaussian and principal curvatures, radial distances, patch areas etc. These features are then compressed into histograms, or estimated...
Small unmanned aerial vehicles (UAVs) have become increasingly popular in the last several years. This paper explores numerous methods to detect and track small UAVs using computer vision.
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...
In computer vision extracting an object from an image automatically is too hard. Towards addressing this issue a comprehensive analysis of most of the Object detection through different Segmentations is performed taken from the major recent publications covering various aspects of the research in this area. We identify the following methods of the state-of-the-art techniques in which an object can...
This paper presents an approach to detect moving and static objects occurring in a video by a novel model-based tracking. The method exploits the spatial and motion coherence of objects across image frames that results from the known bounded shape distortion and object's velocity between two consecutive frames. The interframe transformation space is thus reduced to a reasonable small space of only...
A novel contour grouping method was recently proposed for the difficult task of detecting and delineating unexpected multi-part objects of unknown specific shape and appearance in a variety of natural images. This method, in many ways original and unique, was generally able to obtain object-level groups of quite good quality for a variety of objects and images. For each tested image, a number of object-level...
In this paper, we present a non-symmetry and anti-packing object pattern representation model (NAM). The NAM model codes the geometry of generic object categories as a hierarchy of sub-patterns and each sub-pattern is represented by a rich set of image cues. The sub-pattern-based NAM model is designed to decouple variations due to affine warps and other forms of shape deformations. The combination...
Human movement analysis is a long-studied, but still important and challenging research area in visual surveillance. It involves many fundamental problems in computer vision such as human detection, segmentation and tracking, and higher level problems such as human gesture, action and event recognition. Shape is the most dominant cue for detecting humans due to large appearance variability. In this...
In this paper, we address the problem of estimating the 3D structure and motion of a non-rigid object based on feature points throughout a image sequence. The main limitation of existing factorization methods is that they are difficult to provide correct structure and motion estimates: the motion matrix has a repetitive structure which is not represented by these methods. In order to cope with this...
An approach toward pedestrian detection applied to natural images using improved Random Forest (RF) is proposed. We take a more discriminative method for object part detection by applying the feature of pixel-based. We firstly train a pedestrian random forest which directly maps the image patch appearance to the probabilistic vote about the possible location of the object centroid. For a testing image...
Non-rigid object detection is a challenging open research problem in computer vision. It is a critical part in many applications such as image search, surveillance, human-computer interaction or image auto-annotation. Most successful approaches to non-rigid object detection make use of part-based models. In particular, Conditional Random Fields (CRF) have been successfully embedded into a discriminative...
In this paper, we present a non-symmetry and anti-packing object pattern representation model (NAM) for object detection. A set of distinctive sub-patterns (object parts) is constructed from a set of sample images of the object class; object pattern are then represented using sub-patterns, together with spatial relations observed among the sub-patterns. Many feature descriptors can be used to describe...
As the global threat of terrorism continues to escalate, finding efficient ways to ensure the safety of the public is becoming a major concern for the authorities. This paper presents an investigation of scanning and detection of concealed weapons with possible applications in high risk areas like airports. Using a passive and non-intrusive scanning method like Infrared (IR) imaging, and combining...
Nowadays dexterous manipulation of rigid objects using a robot hand can be achieved fairly well. However, grasping and manipulating deformable objects is still challenging as the force and tactile sensors which are commonly used in such applications can only provide local information about the deformation at the contact points. In this paper, a vision framework is proposed for 3D visually guided grasping...
We present a new object segmentation method that is based on active contours with combined saliency map.It is known that using saliency region can easily get the approximately location of the desired object in the map.In this paper,we use the saliency map to distinguish the desired object from the image when the background is full of noise,and then,to ensure the initial evolving curve in the active...
This paper presents the results of an all-day-long pedestrian classification system based on an AdaBoost cascade meta-algorithm. The underlying idea is to use a Haar-features-based AdaBoost together with an ad-hoc-features-based AdaBoost system in order to reach a better pedestrian classification. A specific night-time pedestrian classification is developed in order to obtain a system that can be...
A basic step in the development of advanced driver assistance systems is the perception and interpretation of information on the vehicle environment. In many cases, the upcoming road geometry in front the own vehicle is of particular interest. Although a prediction of the course of the road can be provided based on map data, the accuracy is not sufficient for most driver assistance systems. The goal...
Intelligent vehicle lighting systems aim at automatically regulate the headlights' beam angle so as to illuminate as much of the road ahead as possible, while avoiding dazzling other drivers. A key component of such a system is a computer vision software able to distinguish blobs due to vehicles' head and rear-lights from those originating from road lamps and reflective elements like poles and traffic...
This paper presents a fruit size detecting and grading system based on image processing. After capturing the fruit side view image, some fruit characters is extracted by using detecting algorithms. According to these characters, grading is realized. Experiments show that this embedded grading system has the advantage of high accuracy of grading, high speed and low cost. It will have a good prospect...
Basically, detecting convex and concave points on the boundary of an object plays an important role in computer vision, object recognition and image understanding. In this paper a method that combines boundary and skeleton information for detecting these critical points is proposed. Specifically, the method is developed with the aim of obtaining high performance and efficiency, and producing a more...
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