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.
This paper proposes a modified selective search method that generates object proposals on RGB-D data in indoor scenes. The proposed method first applies color flattening to generate monotonous color variations in RGB image data. Then, from the color-flattened image and depth map data, cost function-based segment grouping and depth segmentation are applied to produce desirable segmentation results...
We propose a novel phishing detection architecture based on transparent virtualization technologies and isolation of the own components. The architecture can be deployed as a security extension for virtual machines (VMs) running in the cloud. It uses fine-grained VM introspection (VMI) to extract, filter and scale a color-based fingerprint of web pages which are processed by a browser from the VM's...
In this paper we propose a method to add scale-invariance to line descriptors for wide baseline matching purposes. While finding point correspondences among different views is a well-studied problem, there still remain difficult cases where it performs poorly, such as textureless scenes, ambiguities and extreme transformations. For these cases using line segment correspondences is a valuable addition...
In this paper, we present novel approach for text extraction. In computer vision r esearch area, text is very important in images. Here we use edge based extraction of text using ISEF (infinit e symmetrical edge filter). ISEF is optimal edge det ector which gives accurate results for text in imag es. Text extraction involves detection, localization, tracking and enhancement. Large numbers of te chnique...
This paper presents an evaluation of the SIFT (scale invariant feature transform), Colour SIFT, and SURF (speeded up robust feature) descriptors on very low resolution images. The performance of the three descriptors are compared against each other on the precision and recall measures using ground truth correct matching data. Our experimental results show that both SIFT and colour SIFT are more robust...
This paper is about scale-space image trees. We introduce here a variant of the sieve algorithm to produce sieve complement trees where not only extremal regions are characterized but also their corresponding complements. Different simplification methods can transform (or prune) the hierarchy into a simpler form where the remaining nodes represent regions that are noticeably different from their neighbourhood,...
In the field of image analysis and retrieval, the representations based on the shape of edge or boundary can be used to model complex forms and properties. In this paper, we give a detailed description of a new shape feature of edge or boundary, the jag-wave feature, which is usually treated as noise in image processing. The jag-wave feature is defined as a special kind of jagged or waved edge or...
Accurately counting people waiting at bus stops is essential for automated bus fleet scheduling and dispatch. Estimating the passenger demand in regular open bus stops is a nontrivial problem because of the varying conditions, such as illumination, crowdedness, people poses, to name a few. This paper presents a simple, but very effective approach to estimate the passenger count using people density...
A combined texture- and color-based skin detection is proposed in this paper. Nonsubsampled contourlet transform is used to represent texture of the whole image. Local neighbor contourlet coefficients of a pixel are used as feature vectors to classify each pixel. Dimensionality reduction is addressed through principal component analysis (PCA) to remedy the curse of dimensionality in the training phase...
In this paper, we propose a co-learning particle filter approach for vehicle tracking, which is very important for intelligent vehicle. The proposal distribution of the particle filter is a combination of an extra support vector machine (SVM) detector and the motion prior. Previous works focusing on how to online update the detector or the observation likelihood using the tracking results. These approaches...
As infrared focal plane arrays (FPAs) have evolved from the first generation of linear arrays to the second generation of small format staring arrays to the present "third-gen" devices, there is an increased emphasis on large area focal plane arrays with multicolor operation and higher operating temperature. In this paper, we will discuss how one needs to develop an increased functionality...
Otsupsilas thresholding method (OTM) is one of the most commonly used thresholding methods. Unfortunately, the threshold obtained by OTM is biased in favor of the class, whose standard deviation or quantity of data is larger. Besides, one may adopt distinct thresholds in different applications for a same data set. Accordingly, this paper proposes an adaptable threshold decision method (ATDM) to provide...
Interest points are local properties of an image with high informational content. In this paper, we present a new method for image retrieval based on color and distribution of interest points. Firstly, we use Harris corner detector to extract interest points. Secondly, we design a 2D histogram based on interest points to describe an image, which not only takes the local color feature into consideration,...
Local image descriptors computed in areas around salient points in images are essential for many algorithms in computer vision. Recent work suggests using as many salient points as possible. While sophisticated classifiers have been proposed to cope with the resulting large number of descriptors, processing this large amount of data is computationally costly. In this paper, computational methods are...
This paper presents a human-centered picture slideshow system for mobile users. In contrast to conventional ROIs (region-of-interest) detection based systems, we provide mobile users the freedom of personalizing ROIs in a convenient and effective way. Here, we import a simple human interaction, i.e., only a single click, to give a hint for users' ROIs. First, local saliency map (LSM) is generated,...
This paper describes a system for automatically extracting meta-information on people from videos on the Web. The system contains multiple modules which automatically track people, including both faces and bodies, and clusters the people into distinct groups. We present new technology and significantly modify existing algorithms for body-detection, shot-detection and grouping, tracking, and track-clustering...
This paper reports a method for acquiring the prior probability of human existence by using past human trajectories and the color of an image. The priors play important roles in human detection as well as in scene understanding. The proposed method is based on the assumption that a person can exist again in an area where he/she existed in the past. In order to acquire the priors efficiently, a high...
We present a new method for detecting interest points using histogram information. Unlike existing interest point detectors, which measure pixel-wise differences in image intensity, our detectors incorporate histogram-based representations, and thus can find image regions that present a distinct distribution in the neighborhood. The proposed detectors are able to capture large-scale structures and...
In order to study the rules of network roadpsilas traffic dynamic evolution, it is required to establish a certain kind of traffic status model with topological structure of the road network. Most traditional methods are NOT very suitable to describe the links or the directions of traffic flows. This paper puts forward a new visualized model based on HSI (Hue-Saturation-Intensity) color space, then...
Text in scene images can provide very useful as well as vital information and hence, its detection and recognition is an important task. We propose an adaptive edge-based connected-component method for text-detection in natural scene images. The approach is based on three reasonable assumptions - (i) characters of a particular word are locally aligned in a certain direction (ii) each character is...
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.