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We present a novel unsupervised learning method for human action categories from video sequences using Latent Dirichlet Markov Clustering (LDMC). Video sequences are represented by a novel "bag-of-words" representation, where each frame corresponds to a "word". The algorithm automatically learns the probability distributions of the words and the intermediate topics corresponding...
Visible watermarking mechanism often used to claim the copyright of the protected media from the human visual perception. As a result of the visible logo superposes the media content, the visible logo inevitable distorts the content and degrades the readability of digital media. To diminish the visual distortion but preserve the advantages of visible watermarking technique, in this paper, we proposed...
In this paper, we propose a watermarking algorithm for colour image, concept of visual cryptography extended to digital watermarking based on VSS algorithm. An image which has to be transmitted (watermark) is split into two sheet-images using visual secret sharing algorithm. Then, one sheet-image are embedded into the host image blue component before transmission and second sheet-image is held by...
Spatio-Temporal Interest Point (STIP) has been widely used for human action recognition. However, the performance of the STIP based methods are still limited in realistic datasets which often include large variations in illuminations, viewpoints and camera motions. One reason of the low performance is that the STIPs only reflect the local change in videos, which is not enough to obtain stable informative...
The efficient browsing and retrieval of videos is a fundamental part of current multimedia systems especially on mobile devices. One way to provide enjoyable video browsing to the users is by providing summaries of the videos whereby the users can have a clue of the contents of the video before watching the video itself. In this paper, we propose a key frame extraction based video summarization technique...
The bag-of-words approach with local spatio-temporal features have become a popular video representation for action recognition. Recent methods have typically focused on capturing global and local statistics of features. However, existing approaches ignore relations between the features, particularly space-time arrangement of features, and thus may not be discriminative enough. Therefore, we propose...
The notion of Visual Cryptography was first introduced by Naor and Shamir in 1994 [NS94]. Here “visual” means that the decryption is done by human eyes instead of by any computing devices. To retrieve the ciphertext, simply stack the encrypted images together. In fact, it is more like an image secret sharing scheme than an encryption scheme. Both the secret and the shares are black-and-white pictures,...
The growing number of textual reports poses a great challenge for investigative analysis. However, text visualization has the potential to address this problem by automating the analysis of text reports, thus reducing workloads and providing new insights for crime analysts. We are developing a crime report visualization system for such investigative analysis. Our system leverages natural language...
Universal Networking Language (UNL) is an artificial language for computers to represent human language using graphs. UNL system consists of UNL Ontology, which provides the semantic background for each Universal Words (UWs) or concepts. UNL Ontology includes possible relations between UWs, UWs definition and UNL system hierarchy. UNL Ontology store all these information in a lattice structure, where...
In order to obtain a better human-machine engineering implementation effect and get a faster feedback during the bridge designing, the paper suggested a virtual simulation and evaluation method. And by using of the software Visual C++, MultiGen and Vega, an evaluation simulation system was also built. Such a system can display the whole layout of the bridge, evaluate the key human-machine designing...
This paper presents a novel approach called PEPA (Perceptual Edges Preservation Algorithm) which enables computing machines to mimic the human vision capability in perceiving meaningful objects in an input scene, characterized in that the preserved edges are conformal to human vision perception. The approach mainly comprises three stages: (1) applying linear and nonlinear filtering to mimic the capability...
Infrared Sensors are widely used nowadays on Aircrafts (rotary and fixed wing) to help pilot's activities. The infrared information of the surrounding area are used mainly for two different purposes: Navigation and Search & Track-While-Scan. Navigation functions, commonly identified with the name of Imaging Modes, are devoted to aid pilots in conjunction with advanced human machine interfaces...
Using brain-computer interfaces (BCIs) to improve human performance has become a state-of-the-art research topic. The concept of collaborative BCIs, which aimed to use multi-brain computing to enhance human performance, was proposed recently. To further study the feasibility of collaborative BCIs, here we propose to develop an online collaborative BCI to accelerate human response to visual target...
In this paper we present a salient object detection model from an over-segmented image. The input image is initially segmented by the mean-shift segmentation algorithm and then over-segmented by a quad mesh to even smaller segments. Such segmented regions overcome the disadvantage of using patches or single pixels to compute saliency. Segments that are similar and spread over the image receive low...
In this paper, we present a model for learning atomic actions for complex activities classification. A video sequence is first represented by a collection of visual interest points. The model automatically clusters visual words into atomic actions based on their co-occurrence and temporal proximity using an extension of Hierarchical Dirichlet Process (HDP) mixture model. Our approach is robust to...
Wide area monitoring for community and city can be a very challenging engineering task due to its scale and heterogeneity in sensor, algorithm, and visualization levels. Multi-modal cameras and algorithms have to be fused into compact presentation for a single operator to actively and effectively respond to anomaly events and jeopardy. This paper presents a distributed and scalable video surveillance...
Kinect, as a 3D digital capturing device, can collect the RGB and depth information of human activities rapidly. We study fusing the depth and RGB information for activity recognition. We introduce histogram color-based image thresholding to detect skin on human body, and use a GMM model to segment human hand areas. We design a new local descriptor, called a 3D Motion Scale-Invariant Feature Transform...
Visual discomfort has been the subject of considerable research in relation to stereoscopic displays, but remains an ambiguous concept used to denote a variety of subjective symptoms potentially related to different underlying processes. In this paper, we firstly studied the hue and saturation influence quantitatively on stereoscopic images combining the characters of human visual system (HVS). According...
In this paper, a simple method to extract regions of interest (ROI) from images is proposed. In the field of image processing, intensity, color and orientation are commonly used features for saliency map generation in most visual attention model. However, texture feature can contribute to the guidance of attention in a bottom-up model. We consider texture contrast as a component of final saliency...
The ability to make good decisions is important to people in all areas of lives. This is also evident in sports games where players have a very limited time to obtain, interpret and analyze information on ever-changing situations before they decide on their actions. Using common basketball game scenarios, this research compares and evaluates decisions made by novice and experienced basketball players...
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