The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Manual analysis of large volumes of video surveillance footage stemming from the widespread deployment of security cameras is error prone, expensive and time consuming. Despite the commercial availability of software for automated analysis, many products lack third party extensibility, the capability to perform simultaneous event detection and have no provision for anomaly detection in highly dense...
Corner detection is a important task in low level vision. Detecting corners helps one to establish similarity between two or more images. Traditional approaches for corner detection involve finding significant variation around a pixel neighbourhood in two different directions. In this work, we have developed a novel framework to detect corners in a given image by learning corners from images corresponding...
This paper presents a new methodology to extract discriminative features from images, that are robust and invariant to image blur and JPEG compression. The local patches are quantized in the polar geometric structure using Log Polar Transformation (LPT). Then two-dimensional Discrete Wavelet Transformation (DWT) is used to decompose the polar structured patch into sub-bands. Each approximation sub-band...
This paper presents a method to deal with the multi-body segmentation problem using a set of 2D points matches between two views. The key feature of our approach is the explicit inclusion of a higher semantic information as given by general purpose object detectors that boost the segmentation of the moving objects. In the classical formulation of the problem, only 2D matched points between views are...
Understanding how human emotion is evoked from visual content is a task that we as people do every day, but machines have not yet mastered. In this work we address the problem of predicting the intended evoked emotion at given points within movie trailers. Movie Trailers are carefully curated to elicit distinct and specific emotional responses from viewers, and are therefore well-suited for emotion...
The paper presents two advanced methods for comparative study in the field of computer vision. The first method involves the implementation of the Scalar Invariant Fourier Transform (SIFT) algorithm for the leaf recognition based on the key descriptors value. The second method involves the contour-based corner detection and classification which is done with the help of Mean Projection algorithm. The...
As an alternative to vector-based descriptors, such as SIFT and SURF, more computationally efficient binary descriptors, such as BRISK and ORB, have recently been proposed. These binary descriptors are usually used in combination with a novel scale-space FAST-based detector to be suitable for real-time applications, but it consumes more time than creating binary descriptors. Therefore, if accuracy...
Objectness measure, which generates some candidate object proposals, has been shown to accelerate the traditional sliding window category-dependent object detection methods. Binarized Normed Gradients (BING) is one of the state-of-the-art detectors. It achieves high object detection rate (DR), but moderate object overlap rate (OR) because the candidate proposals produced by BING are fixed-sized. In...
Tracking-by-detection based on online learning has shown superior performance in visual tracking of unknown objects. However, most existing approaches use a fixed-size box to represent objects and can merely show the unoccluded area of the object. To overcome the limitations, we propose a novel tracking-by-detection approach based on local patches. We extend ferns forest to visual tracking and optimize...
This paper presents an efficient feature detection algorithm based on the classical SURF (Speeded Up Robust Feature) detector. The image features are represented and scored with respect to its local symmetry property. The local symmetry has natural properties of scale and transformation invariants, and also insensitive to illumination change and local noise. By the proposed feature descriptor, the...
The importance of choosing a suitable feature detector and descriptor to find the optimal correspondence between two sets of image features has been highlighted. In this direction, this paper presents an evaluation of some well known feature detectors and descriptors; including HARRIS-FREAK, HESSIAN-SURF, MSER-SURF, and FAST-FREAK; in the search for an optimal detector and descriptor pair that best...
This paper presents a novel approach of finding corner features between retinal fundus images. Such images are relatively textureless and comprising uneven shades which render state-of-the-art approaches e.g., SIFT to be ineffective. Many of the detected features have low repeatability (< 10%), especially when the viewing angle difference in the corresponding images is large. Our approach is based...
In this paper, we describe a fully automatic approach for detecting and matching geometrical corner feature correspondences between aerial images with larger scale and view variations. The main assumption of the approach is the fact that many man-made environments contain a large number of parallel linear features. We exploit this observation towards efficient detection and estimation of vanishing...
In this paper, we propose an improved method for single image haze removal based on the dark channel prior. The dark channel prior is a kind of statistics of outdoor haze-free images. It estimates the transmission map and gives out a superior result. While refining the transmission map with soft matting is computation consuming and this prior is invalid for near white scenes. We simplify the refining...
In this research paper Objects are detected and recognized in cluttered scene. We use Harris Corner Detector to extract interest points, and use additional descriptor FREAK (Fast Retina Keypoint) to match and find detect the object. We also use some classification algorithm to classify and label the object based on the extracted features. The proposed techniques are precise and robust.
The naked eye is capable of perceiving electromagnetic radiation in a narrow band of frequencies, known as the optical spectrum. Working with low energy radiation outside the optical spectrum presents distinct difficulties, requiring the use of apparatus to measure invisible and intangible electromagnetic radiation. The apparatus, incorporating a Wiimote, and associated method are presented for a...
Data from satellite and aerial images are now widely used by everyone. These images contain information from different frequency bands that help to characterize areas of interest. In this paper we study a framework for object detection in aerial image based on discriminatively-trained models trained on multimodal data. Specifically, we investigate a method to merge outputs of large margin classifiers...
This article presents an improved feature matching method based on gradient constraint. SIFT is regarded as one of the most powerful features because of the conspicuous invariance of image rotation, noise and illumination. However, there will still be many mismatches when SIFT features are matched across images, especially when the amount of features is very large. In order to reduce the number of...
We present a novel method for junction detection. A junction is defined as the point where several lines intersect. Given the line segments in the image, our junction detector consists of three steps. First, potential junctions are located from a small neighborhood around the intersection of each pair of lines. Second, our detector searches the branches connecting to each potential junction in a circular...
In order to present an aerial refueling drogue detector, we use a sliding-window object detection framework, while using hybrid features of the sub-image in the detecting windows. Image processing technique and wavelet filter technique are used in the process of feature extraction, to form hybrid feature set. Feature selection depending on AdaBoost is used in the process of feature subset selection...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.