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Evolutionary computation has often been presented as a possible model for creativity in computers. In this theoretical paper, preparing for a series of experiments, evolution is discussed in the light of a theoretical model of human artistic process, recently presented by the author. Some crucial differences between human artistic creativity and natural evolution are observed and discussed, also in...
Product model enhances engineering work by the application of techniques such as modeling by features, contextual definition of engineering objects, application of active knowledge, and real time analysis of product modification consequence. These achievements are efficient in local product definition where small number of parts is considered. However, decision on a single product object in large...
We introduce global regularities in the 2.5D building modeling problem, to reflect the orientation and placement similarities between planar elements in building structures. Given a 2.5D point cloud scan, we present an automatic approach that simultaneously detects locally fitted plane primitives and global regularities. While global regularities are extracted by analyzing the plane primitives, they...
Mobility models play a crucial role in mobility wireless networks with respect to evaluating the network protocols and performances. However, the majority of existing mobility models either does not exhibit realistic movement characteristics or modeling methods are too complex. In this paper, a new mobility model based on Location Attraction (LAMM) is proposed, which utilizes human's clustering features...
We present an approach to automatically learn the visual appearance of an environment in terms of object classes. The procedure is totally unsupervised, incremental, and can be executed in real time. The traversability property of an unseen object is also learnt without human supervision by the interaction between the robot and the environment. An incremental version of affinity propagation, a state-of-the-art...
This paper presents a probabilistic framework combining heterogeneous, uncertain, information such as object observations, shape, size, appearance of rooms and human input for semantic mapping. It abstracts multi-modal sensory information and integrates it with conceptual common-sense knowledge in a fully probabilistic fashion. It relies on the concept of spatial properties which make the semantic...
For robots of the future to interact seamlessly with humans, they must be able to reason about their surroundings and take actions that are appropriate to the situation. Such reasoning is only possible when the robot has knowledge of how the World functions, which must either be learned or hard-coded. In this paper, we propose an approach that exploits language as an important resource of high-level...
The integration of physical systems and processes with networked computing has led to the emergence of a new generation of engineered systems, called Cyber-Physical Systems (CPS). The resources in these systems are critical, because without them timely and dependable CPS services in different contexts cannot be provided. This in turn requires a formal resource model integrated within a CPS service...
This article presents a robust, real-time background subtraction algorithm able to operate properly in complex dynamically changing visual conditions and indoor/outdoor environments, based on a single, cheap monocular camera, like a webcam. This algorithm uses an image grid and models each pixel of the grid as a mixture of adaptive Student-t distributions. This approach makes this algorithm robust...
We had proposed a general model for WSD which is novel in some interesting ways and we have customized the model in form of a method (algorithm group) which is further customized in form of a number of algorithms to study the model's capability. We have introduced an optimization which has resulted in an unsupervised system which is the second best when evaluated against the renowned Senseval-3 international...
Using language involves more than exchanging information through a combination of words. Emotional elements in language can strongly influence the meaning of conversational actions which goes beyond the simple exchange of information. To evaluate current emotion models, we study how they deal with situations that arise in conversations (e.g. the intentions of a speaker). We will give insights on how...
Affective, ‘emotional’ as widely known, gaming, constitutes the new frontier for game design and development. The ultimate goal is being able to read the emotional state of a gamer and use it to change the game in such a way so as to provide to him/her a more immersive experience, a better gameplay. However, existing affective gaming approaches use specialized sensors in order to extract behavioral...
Users' mental models of security, though possibly incorrect, embody patterns of reasoning about security that lead to systematic behaviors across tasks and may be shared across populations of users. Researchers have identified widely held mental models of security, usually with the purpose of improving communications and warnings about vulnerabilities. Here, we implement previously identified models...
The synthesis of multi-fingered grasps on nontrivial objects requires a realistic representation of the contact between the fingers of a robotic hand and an object. In this work, we use a patch contact model to approximate the contact between a rigid object and a deformable anthropomorphic finger. This contact model is utilized in the computation of Independent Contact Regions (ICRs) that have been...
Accurate 3D models of the human brain vessels can greatly help to diagnose serious diseases. Such models can be constructed by segmentation of 3D MRA images, especially the recently introduced high resolution 7T MRA. We propose a new two-step approach for fully automatic segmentation of 7T MRA images of the human cerebrovascular system. First, a 3D model-based approach is applied to segment thick...
Accurate inter-subject registration of magnetic resonance (MR) images of the human brain is required to allow meaningful comparisons across groups of subjects. Some anatomical structures can be very difficult to match and this can result in intensity based registration approaches inferring complex and implausible mappings in some regions. In this work, we propose a generic probabilistic framework...
Object Tracking is an important task in video processing because of its variety of applications in visual surveillance, human activity monitoring and recognition, traffic flow management etc. Multiple object detection and tracking in outdoor environment is a challenging task because of the problems raised by poor lighting conditions, variation in poses of human object, shape, size, clothing, etc....
Simulations of statistical models have been used to validate theories of past events in evolution of species. Studies concerning human evolution are important for understanding about our history and biodiversity. However, these approaches use complex statistical models, leading to high computational cost. The present paper proposes optimization techniques for Hyper-threaded multicore architectures...
This work presents a robust method for realtime segmentation and tracking of moving objects using depth image sequences, which is insensitive to illumination changes. We propose a novel criterion in our quadtree split-and-merge framework and effectively solves the problem of segmenting objects in complex and cluttered scenes. We also introduce a plane estimation algorithm to cope with the indistinction...
Software development is the most central challenge in present day robot system development. This challenge is even more demanding in multi robot systems interacting via one or many connectivity clouds. There is a demand for an overall improvement in the way the robotic software development is done today. This demand is even more critical for cloud based multi robot systems. This article describes...
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