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.
In this paper, we propose a thermal image based measurement technique for the volumetric flow rate of a liquid inside a thin tube. Our technique makes use of the convection heat transfer dependency between the flow rate and the temperature of the flowing liquid along the tube. The proposed method can be applied to diagnose superficial venous disease non-invasively by measuring the volumetric blood...
X-ray imaging has been developed not only for its use in medical imaging for human beings, but also for materials or objects, where the aim is to analyze (nondestructively) those inner parts that are undetectable to the naked eye. Thus, X-ray testing is used to determine if a test object deviates from a given set of specifications. Typical applications are analysis of food products, screening of baggage,...
In order to reduce the security risk of a commercial aircraft, passengers are not allowed to take certain items in their carry-on baggage. For this reason, human operators are trained to detect prohibited items using a manually controlled baggage screening process. In this paper, we propose the use of an automated method based on multiple X-ray views to recognize certain regular objects with highly...
We present a variational framework for naturally incorporating prior shape knowledge in guidance of active contours for boundary extraction in images. This framework is especially suitable for images collected outside the visible spectrum, where boundary estimation is difficult due to low contrast, low resolution, and presence of noise and clutter. Accordingly, we illustrate this approach using the...
In this paper we tackle the challenging problem of multimodal feature selection and fusion for vehicle categorization. Our proposed framework utilizes a boosting-based feature learning technique to learn the optimal combinations of feature modalities. New multimodal features are learned from the existing uni-modal features which are initially extracted from the data acquired by a novel audio-visual...
This paper presents a smart lighting control system based on human motion tracking. Proper illumination and color temperature depend on human activities. A smart lighting system that provides automatic control of lighting illumination and color temperature needs to track human motion and understand human activities. Infrared and thermal spectrum provides useful information robust to the lighting condition...
Medical image search is a significant way to provide similar clinical cases for doctors. Text based and content based image retrieval techniques have been widely investigated in the last decades. However, handling text-missing images and large scale medical database is still challenging. Traditional methods may encounter unsolvable efficiency problem or storage problem when tackling millions of images...
Wide Area Aerial Surveillance (WAAS) produces very large images at 1-2 fps or more. This data needs to be processed in real time to produce semantically meaningful information, then queried efficiently. We have designed and implemented a full system to detect and track vehicles, and infer activities. We address here the scalability issues, and propose solutions to have the tracker run in real time...
With image capturing technology growing ubiquitous in consumer products and scientific studies, there is a corresponding growth in the applications that utilize scene structure for deriving information. This trend has also been reflected in the plethora of recent studies on reconstruction using robust structure from motion, bundle adjustment, and related techniques. Most of these studies, however,...
An effective way to improve the quality of image retrieval is by employing a query-dependent similarity measure. However, implementing this in a large scale system is non-trivial because we want neither hurting the efficiency nor relying on too many training samples. In this paper, we introduce a query-dependent bilinear similarity measure to address the first issue. Based on our bilinear similarity...
While it is important to digitize heritage sites 'as is', building 3D models of damaged archaeological structures can be visually unpleasant due to the presence of large missing regions. This work addresses intensity filling-in, or intensity inpainting, of such large damaged regions post geometric reconstruction. Assuming a Lambertian image formation model, we first establish that patches corresponding...
Duplicate image discovery, or discovering duplicate image clusters, is a challenging problem for billions of Internet images due to the lack of good distance metric which both covers the large variation within a duplicate image cluster and eliminates false alarms. After carefully investigating existing local and global features that have been widely used for large-scale image search and indexing,...
We focus on the problem of mining object categories from large datasets like Google Street View images. Mining object categories in these unannotated datasets is an important and useful step to extract meaningful information. Often the location and spatial extent of an object in an image is unknown. Mining objects in such a setting is hard. Recent methods model this problem as learning a separate...
A new algorithm meant for biomedical image retrieval application is presented in this paper. The local region of image is represented by peak valley edge patterns (PVEP), which are calculated by the first-order derivatives in 0º, 45º, 90º and 135º directions. The PVEP differs from the existing local binary pattern (LBP) in a manner that it extracts the directional edge information based on first-order...
With the advent of huge collection of images from Internet and emerging mobile devices, large-scale image classification draws amount of research attention in computer vision and AI communities. The advancement of large-scale image classification largely depends on solutions to two problems: how to learn good feature representation from variant scales of pixels, and how to create classification models...
Big Data analysis is an emerging topic in computer vision and pattern recognition. As one example problem of big data, we study semantic age labels and facial aging pattern analysis on a large database. In aging analysis, one of the great challenges is the lack of a large number of face images with ground truth age labels. Unlike many other example-based recognition problems where human annotations...
We propose a set of features derived from skeleton tracking of the human body and depth maps for the purpose of action recognition. The descriptors proposed are easy to implement, produce relatively small-sized feature sets, and the multi-class classification scheme is fast and suitable for real-time applications. We intuitively characterize actions using pairwise affinities between view-invariant...
Over the last few years, with the immense popularity of the Kinect, there has been renewed interest in developing methods for human gesture and action recognition from 3D data. A number of approaches have been proposed that extract representative features from 3D depth data, a reconstructed 3D surface mesh or more commonly from the recovered estimate of the human skeleton. Recent advances in neuroscience...
Recently released depth cameras provide effective estimation of 3D positions of skeletal joints in temporal sequences of depth maps. In this work, we propose an efficient yet effective method to recognize human actions based on the positions of joints. First, the body skeleton is decomposed in a set of kinematic chains, and the position of each joint is expressed in a locally defined reference system...
We present a novel approach to 3D human action recognition based on a feature-level fusion of spatiotemporal features and skeleton joints. First, 3D interest points detection and local feature description are performed to extract spatiotemporal motion information. Then the frame difference and pairwise distances of skeleton joint positions are computed to characterize the spatial information of the...
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.