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.
Software-Defined Networking (SDN) is an emerging network architecture that enables network programmability. Recent research activities on SDN make it important to develop an emulator that accurately emulates OpenFlow-enabled SDN networks. However, existing emulators and simulators focus on either data plane performance or software switches. This motivates us to develop a network emulator that provides...
Intracoronary optical coherence tomography (OCT) is a new invasive imaging system which produces highresolution images of coronary arteries. Preliminary data suggests that the atherosclerotic disease can be detected from the intracoronary OCT images. However, manual assessment of the intracoronary OCT images is time-consuming and subjective. In this work, we present an automatic atherosclerotic disease...
Most current approaches in action recognition face difficulties that cannot handle recognition of multiple actions, fusion of multiple features, and recognition of action in frame by frame model, incremental learning of new action samples and application of position information of space-time interest points to improve performance simultaneously. In this paper, we propose a novel approach based on...
In this paper, we propose a framework which fuses multiple features for action recognition in depth sequence. The fusion of multiple features is important for recognizing action since a single feature-based representation is inadequate to capture the variants. Hence, we use two types of features: i) a quantized vocabulary of local spatio-temporal descriptor HOG3D, and ii) a global projection based...
Real-time 3D sensing has many important applications in areas such as robotic navigation, virtual reality and human-computer interaction. A variety of techniques have been developed for the determination of 3D geometry information such as binocular vision, structured light and their combination. However, existing non-contact optical 3D sensing approaches have their own limitations in the process of...
Scene classification is useful for automatic organization of personal digital photographs or visual guidance of robots, but it is a time consuming and labor-intensive task to label adequate examples to train robust classifiers. Active learning is a key technique to reduce human-labeling burden by exploring an optimal subset from unlabeled data. In this paper we use a batch mode incremental and active...
We explore feature selection methodology for automatic Pathological Myopia detection via learning from an optimal set of features. An mRMR optimized classifier is trained using the candidate feature set to find the optimized classifier. We tested the proposed methodology on eye records of approximately 800 subjects collected from a population study. The experimental results demonstrate that the new...
Optic cup is the primary image indicator clinically used for identifying glaucoma. To automatically localize the optic cup in fundus images, an effective and efficient superpixel classification based approach is proposed in this work, which maintains both advantages of existing pixel and window based approaches. This method provides three major contributions. First, it proposes processing of the fundus...
Peripapillary atrophy (PPA) is an atrophy of preexisting retina tissue. Because of its association with eye diseases such as myopia and glaucoma, it is important to determine the presence of PPA clinically. Experienced ophthalmologists are able to determine the presence of PPA using visual information from the retinal images. However, it is tedious, time consuming and subjective to examine all images...
Reliable estimation of crowd density in public plays an important role on intelligent surveillance in recent years. There have been a lot of research on people counting; however, most of them only consider crowd with slight occlusions and their algorithms usually accompany with high computational complexity. In this paper, we present a simple model based on image potential energy to estimate the crowd...
Glaucoma is an optic nerve disease resulting in the loss of vision. There are two common types of glaucoma: open angle glaucoma and angle closure glaucoma. Glaucoma type classification is important in glaucoma diagnosis. Clinically, ophthalmologists examine the iridocorneal angle between iris and cornea to determine the glaucoma type as well as the degree of closure. However, manual grading of the...
The accuracy and speed of laser spot center detection algorithm directly affect the efficiency and the application range of the measurement. This paper proposes a novel laser spot center detection method based on the laser spot's geometry feature. This method firstly extracts the contour by detecting the spot image, then further optimizes the extracted contour according to the geometric characteristics...
Otsu method is proper to deal with two conditions: (1) two or more classes with distintive gray-values respectively; (2) classes without distinctive gray-values, but with similar areas. However, when the gray-value differences among classes are not so distinct, and the object is small relative to backgroud, the separabilities among classes are insufficient. In order to overcome the above problem,...
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.