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We are looking to perform anomaly detection in video streams, within the fastest time possible, and without the need to hand-engineer features to suit for particular scenes. In any scene captured by surveillance camera, there could be single or multiple persons (agents) and activities ongoing concurrently, with or without human-object and/or human-human interactions. These characteristics lead to...
Observing human activities can reveal a lot about the structure of the environment, the objects contained therein and also their functionality. This knowledge, in turn, can be useful for robots interacting with humans or for robots performing mobile manipulation tasks. In this paper, we present an approach to infer the geometric and functional structure of the environment and the position of certain...
The increasing use of smartphones to access sensitive and privacy data has given rise to the need of secure authentication technique. Existing authentication mechanisms on smartphones can only provide one-time verification, but the verified users are still vulnerable to the session hijacking. In this article, we propose a transparent and continuous authentication system based on users' touch interaction...
This paper provides a unified background of probabilistic modeling methods which should serve to model-based fault detection (FD). This background should help in orientation within within the set of the problems to be addressed when developing a novel method as well as within a wide set of available methods and in recognition of their suitability to a particular problem in hands.
Learning robots are faced with two major issues: identification of the dynamics of the robot and identification of the environment as well as its interaction with the robot. We discuss in this paper a way to acquire representations of both these concepts through an iterative learning procedure. Furthermore we will concentrate on qualitative representations, since we are not necessarily interested...
Target motion analysis (TMA) for a rectilinear source movement (RSM) has been intensively studied in the last ten years. But difficulties still exist, especially when source heading or speed changes are within the same time as the conventional TMA convergence time. This paper is concerned with a new method of batch TMA for maneuvering sources using a non-linear least-squares fit between the whole...
Monitoring the dynamical behavior of receptors and lig-ands via single-molecule fluorescence microscopy allows quantifying the interactions between these two subcellular structures at a very high spatial and temporal resolution. We have developed a probabilistic approach to determine the positions of receptors and ligands over time in two-channel image sequences of small protein complexes and single...
Animated movies are a popular way to communicate complex phenomena in cell biology to the broad audience. Animation artists apply sophisticated illustration techniques to communicate a story, while trying to maintain a realistic representation of a complex dynamic environment. Since such hand-crafted animations are time-consuming and cost-intensive to create, our goal is to formalize illustration...
The Multiple Target Tracking (MTT) problem is one of the fundamental challenges in computer vision. In this paper, we propose a feasible detection and association based MTT system which uses a modified Deformable Part-Based Model (DPM) to generate detection results and then links detections into track lets to further form long trajectories. We first describe our modified DPM algorithm which could...
In this paper, a multiple Neural Network (NN) compensator is designed for a billiard robot to finish a task, in which the trained robot is commanded to control the cue ball to a specific target point along a trajectory with multiple cushion rebounds. A novel pyramid classification has been established to sort out the pattern of trajectory and its segments. For each trajectory pattern, a corresponding...
As technology to connect people across the world is advancing, there should be corresponding advancement in taking advantage of data that is generated out of such connection. To that end, next place prediction is an important problem for mobility data. In this paper we propose several models using dynamic Bayesian network (DBN). Idea behind development of these models come from typical daily mobility...
This paper is devoted to the problems of information systems necessary for constructive data classification and decision-making process of operator depending on the cognitive characteristics.
Online multi-object tracking with a single moving camera is a challenging problem as the assumptions of 2D conventional motion models (e.g., first or second order models) in the image coordinate no longer hold because of global camera motion. In this paper, we consider motion context from multiple objects which describes the relative movement between objects and construct a Relative Motion Network...
Hap tics refers to a tactile feedback technology which allows users to touch and feel objects in virtual environments. However, it is hard to share the visual-hap tic experience, which relies too much on the computer hardware and the hap tic virtual environment software. In our previous work, we proposed a new system which intends to record and playback visual-hap tic information from hap tic virtual...
Tracking trajectory of three-dimensional trees is a difficult problem in computer animation and virtual reality. It requires not only high sense of reality for the morphology of trees and tree moving, but also adequate real-time. In this paper, we present a simulation method based on video data driven. Firstly, split out the main branches and leaves of trees from video images by using hybrid method...
Many factors can affect the predictability of public bus services such as traffic, weather, day of week, and hour of day. However, the exact nature of such relationships between travel times and predictor variables is, in most situations, not known. In this paper we develop a framework that allows for flexible modeling of bus travel times through the use of Additive Models. The proposed class of models...
Trajectory regression, which aims to predict the travel time of arbitrary trajectories on road networks, attracts significant attention in various applications of traffic systems these years. In this paper, we tackle this problem with a multitask learning (MTL) framework. To take the temporal nature of the problem into consideration, we divide the regression problem into a set of sub-tasks of distinct...
In this paper we develop a Bayesian nonparametric Inverse Reinforcement Learning technique for switched Markov Decision Processes (MDP). Similar to switched linear dynamical systems, switched MDP (sMDP) can be used to represent complex behaviors composed of temporal transitions between simpler behaviors each represented by a standard MDP. We use sticky Hierarchical Dirichlet Process as a nonparametric...
Humanoid robots are required to perform a wide repertoire of task working beside humans in complex dynamic environments. Learning mechanism are important for building up this type of repertoires of robot skills, however, despite the clear advantages of this approaches it would be impractical to teach the robot skills for every needed task and for every foreseen situation. Robot skills learning approaches...
To equip a robot with various required skills so that to serve human society, plenty of research have been performed and successfully applied from both theoretical and practical aspects for decades. Usually, a robot with several skills needs to recall a different controller or model parameters to fit the new circumstance as task to be fulfilled or environment changes. Therefore, how to smoothly shift...
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