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.
We propose a method for classifying actions involving people interacting with objects. Our method combines motion and appearance information into a unified framework. Here, we explore the video's sparse component as provided by robust principal-component analysis for the extraction of motion information in the form of trajectories. While we use motion as the main clue for classification, we also incorporate...
Head-shoulder detection is widely used in many applications, and robust image descriptors are crucial to the detection performance. In this paper, by exploiting the second-order region covariance descriptor as a complement to widely-used histogram-based descriptors, we propose a new two-stage coarse-to-fine cascade framework to make full use of both types of descriptors for robust head-shoulder detection...
Robust feature plays an important role in many vision based applications. This paper proposes a fast extreme illumination robust feature in affine space. It inherits the techniques of extreme point location and main orientation computation from SIFT (Scale Invariant Feature Transform) algorithm, and adopts the rotation and scale invariant circular binary pattern based histograms in the affine space...
We discuss the properties of a class of latent variable models that assumes each labeled sample is associated with a set of different features, with no prior knowledge of which feature is the most relevant feature to be used. Deformable-Part Models (DPM) can be seen as good examples of such models. These models are usually considered to be expensive to train and very sensitive to the initialization...
We present a new visual descriptor that combines a multi-scale Laplacian Profile with a Radial Discrete Fourier Transform. This descriptor exists at every position and scale in an image and provides a local feature vector that is both discriminant and robust to changes in orientation and scale. It has a variable description length, and thus can be easily adapted for a variety of applications, ranging...
We introduce a known-key scenario for steganalysis and propose an approach to construct highly accurate quantitative detectors within it. As an example we construct a quantitative detector based on the well-known SPAM-features and apply it to steganalysis of non-distorted bitmap images with LSB-matching. While the state-of-the-art methods aiming at solving this problem allow to detect payloads up...
As vehicles travel through a scene, changes in aspect ratio and appearance as observed from a camera (or an array of cameras) make vehicle detection a difficult computer vision problem. Rather than relying solely on appearance cues, we propose a framework for detecting vehicles and eliminating false positives by utilizing the motion cues in the scene in addition to the appearance cues. As a case study,...
A novel sparsity-based sub-pixel anomaly detection framework is proposed for hyperspectral imagery. The proposed approach consists of the following steps. First, a joint sparsity model is utilized to simultaneously represent the surrounding local background pixels and to automatically prune the rough overcomplete dictionary as a reliable, compact base for the following center test pixel representation...
We propose a new geometric super resolving approach that overcomes the geometric resolution reduction caused due to the spatially large pixels of the detection array while the improvement process is obtained by applying axial scanning and a phase retrieving procedure. In the scanning process, several images are captures corresponding to focus made on different axial plains. By applying iterative Gerchberg-Saxton...
An analytical spectral model to efficiently characterize direct power detectors located on the focal plane of focusing THz systems is presented. The model is obtained by extending a Fourier Optics like representation of the electromagnetic field in the focal plane to the THz domain and combining it with a recently developed equivalent network representation. This analytical model is then use to efficiently...
Spectrally Efficient Frequency Division Multiplexing (SEFDM) is a non-orthogonal multicarrier communication technique that can pack more sub-carriers than Orthogonal Frequency Division Multiplexing (OFDM) in a given bandwidth. In this work, we propose a multi-band architecture named Block-Spectrally Efficient Frequency Division Multiplexing (B-SEFDM) for a large non-orthogonal system. Furthermore,...
Spectrally Efficient Frequency Division Multiplexing (SEFDM) is a non-orthogonal multi-carrier communication technique that can pack more sub-carriers than Orthogonal Frequency Division Multiplexing (OFDM) for a given bandwidth. In this paper, we propose a hybrid soft Iterative Detection (ID) together with Fixed Sphere Decoding (FSD) for QAM modulation schemes from 4QAM to 16QAM. In terms of 4QAM,...
Visually perceiving human motion at semantic level is an important however challenging problem in multimedia area. In this work, we propose a novel approach to map the low-level responses from visual detection to semantically sensitive description to human actions. The feature map is triggered by the output of deformable part model detection, in which the critical information about body parts configuration...
This paper presents our system designed for MSR-Bing Image Retrieval Challenge @ ICME 2014. The core of our system is formed by a text processing module combined with a module performing PCA-assisted perceptron regression with random sub-space selection (P2R2S2). P2R2S2 uses Over-Feat features as a starting point and transforms them into more descriptive features via unsupervised training. The relevance...
To gain an in-depth understanding of the behaviour of a malware, reverse engineers have to disassemble the malware, analyze the resulting assembly code, and then archive the commented assembly code in a malware repository for future reference. In this paper, we have developed an assembly code clone detection system called Bin Clone to identify the code clone fragments from a collection of malware...
In this paper, it is shown how the issue of reconstructing time-varying unknown delays for linear systems can be turned into a mode detection one for switched affine systems. The specificities due to this reformulation are highlighted. The property of discernability, that is the ability for a detector to deliver a unique solution, is specifically addressed. An example is given as an illustration of...
Currently there are many multimedia benchmarks and databases available with a predefined set of concepts for which detectors can be formed or are even already available. One can use these background concepts to form semantic concept vectors for each image or video in the database by concatenating the concept prediction outputs. In this paper we investigate the use of such semantic concept features...
In this paper we propose and evaluate a new technique that localizes the description ability of the well established MPEG-7 and MPEG-7-like global descriptors. We employ the SURF detector to define salient image patches of blob-like textures and use the MPEG-7 Scalable Color (SC), Color Layout (CL) and Edge Histogram (EH) descriptors and the global MPEG-7-like Color and Edge Directivity Descriptor...
In this paper, we study iterative detection algorithms of the multi-cell multi-user massive MIMO systems with pilot contamination. First, a iterative algorithm applying soft decision interference cancellation is introduced. It is based on minimum mean square error (MMSE) filter and derived from [1] where it was applied in block transmission. Then, by considering the algorithm complexity, two iterative...
A lifting-free computational method is proposed to solve approximate fault detection and isolation problems for periodic systems using an ℋ2-optimal model matching approach. The synthesis procedure relies on two key computational procedures: a numerically reliable algorithm to determine least order annihilators of periodic systems to reduce the periodic ℋ2-optimal model matching problem to a simpler...
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.