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The concept of a bipolar query, meant as a database query that involves both mandatory and optional conditions, is discussed from the point of view of, first, flexible database querying and, second, some newer approaches to decision making involving affects and judgments, unconventional multicriteria decision making and the modeling of sophisticated user's intentions and preferences of a positive...
We propose a new method for audio-visual sensor fusion and apply it to automatic aggression detection. While a variety of definitions of aggression exist, in this paper we see it as any kind of behavior that has a disturbing effect on others. We have collected multi- and unimodal assessments by humans, who have given aggression scores on a 3 point scale. There are no trivial fusion algorithms to predict...
This paper addresses the problem of extracting perceptually dominant color names of images. Our approach is motivated by the principle that the pixels corresponding to one dominant color name identified by human are often context dependent, spatially connected and form a perceptually meaningful region. Our algorithm first learns the probabilistic mapping from a RGB color to a color name. Then, a double-threshold...
We study the possibility to extend the concept of linguistic data summaries employing the notion of bipolarity. Yager's linguistic summaries may be derived using a fuzzy linguistic querying interface. We look for a similar analogy between bipolar queries and the extended form of linguistic summaries. The general concept of bipolar query, and its special interpretation are recalled, which turns out...
We solve the problem of localizing and tracking household objects using a depth-camera sensor network. We design and implement Kin sight that tracks household objects indirectly -- by tracking human figures, and detecting and recognizing objects from human-object interactions. We devise two novel algorithms: (1) Depth Sweep -- that uses depth information to efficiently extract objects from an image,...
Multiple research has shown the advantage of patch-based or local representation for face recognition. This paper builds on a novel way of putting the patches in context, using a foveated representation. While humans focus on local regions and move between them, they always see these regions in “context”. We hypothesize that using foveated context can improve performance of local region or patch based...
This paper introduces a vision-based motion capture system. Motion capturing technology consists of two categories: model-based tracking and example-based indexing. The motion capturing systems face two challenges: parameter estimation in high-dimensional space and self-occlusion. Our algorithm extends the locality sensitive hashing (LSH) method to find the approximate examples and then estimates...
Although traditional bag-of-words model has shown promising results for action recognition, it takes no consideration of the relationship among spatio–temporal points; furthermore, it also suffers serious quantization error. In this letter, we propose a novel coding strategy called context-constrained linear coding (CLC) to overcome these limitations. We first calculate the contextual distance between...
The main challenge of question answering is that the lack of task structure prohibits the use of simplified assumptions as in task-oriented dialogue systems. This problem was tackled by integrating a dialogue management environment into a question answering system. Firstly, Wizard of Oz studies were conducted to discover how users describe their music information needs in contextual situations as...
Conceptual Landscapes is a paradigm of Knowledge Representation which is grounded on Conceptual Knowledge Processing. Using the mathematical apparatus of Formal Concept Analysis, we discuss several issues related to the study of adverse drug reactions in oncology using conceptual landscapes. We propose a new approach in investigating adverse drug reactions based on the paradigm of Conceptual Knowledge...
Template matching is widely used in pattern recognition and computer vision. However, the performance of traditional template matching approaches is often sensitive to large intraclass variance, occlusion, minor variety of poses, low-resolution conditions, background clutter etc. To resolve the problem, this paper presents a scene context based template matching method, which is inspired from two...
Several studies both in the field of psychology and in the field of physiology relate stress to the difficulty of transferring information from short term memory to medium term memory. This difficulty causes a reduction in personal efficiency and generates heavy frustration as things to do tend to come to mind with no relation to the user current environment, thus further increasing the stress level...
Attempts to put robots to practical use have been increasing, as robot becomes more human-friendly. In the human-robot interaction field, main issues are how variously the robot can express its emotion and how much the expression is socially acceptable. This paper proposes a robot's expression generation method based on the context information and combination of behavior database for emotional interactive...
Humans are able to recognize facial expressions of emotion from faces displaying a large set of confounding variables, including age, gender, ethnicity and other factors. Much work has been dedicated to attempts to characterize the process by which this highly developed capacity functions. In this paper, we propose to investigate local expression-driven features important to distinguishing facial...
We propose a new type of saliency - context-aware saliency - which aims at detecting the image regions that represent the scene. This definition differs from previous definitions whose goal is to either identify fixation points or detect the dominant object. In accordance with our saliency definition, we present a detection algorithm which is based on four principles observed in the psychological...
In this paper, a hierarchical system is proposed for generating personalization action and activity recognition rules. Multi-level decision rule mining approach in our system not only discovers personal habit of device using, but also finds personal pattern of devices operation manner. First, it processes non-sequential procedure, which mines user's historical action database for constructing rules...
This paper investigates using lexical cohesion to generate a moderately fluent semantic summary from a collection of documents written in Chinese. Based on the algorithm of cohesion analysis using the relationship among the words in the HowNet knowledge database, the built system computes concept frequency rather than word frequency as a measurement of importance. It merges the analysis of lexical...
There clearly are important issues associated with the distinction between acted and naturalistic data, but focusing on acting may not be the best way to articulate them. An alternative is to focus on differences of structure which are often (but not always) associated with the distinction. Several such differences relate to the way signs are distributed: simultaneous or sequential appearance; in...
One of the motives for studying faces and gestures is the role that they play in spontaneous, socially rich interaction between humans. If computers are to interact with humans in that mode (or to analyse what they are doing in it), methods of interpreting the non-verbal signals that they use are critical. It is becoming clear that developing those methods requires databases whose complexity is of...
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