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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...
Mobility-aware cloud services such as fleet management systems need to understand the positions of mobile devices accurately in a real-time manner. Generally speaking, positioning accuracy and data traffic load are in a trade-off relation. Highly accurate real-time positioning requires frequent location data upload and hence results in heavy data traffic load. Although not all data are equally important,...
In this paper, we develop a novel framework for action recognition in videos. The framework is based on automatically learning the discriminative trajectory groups that are relevant to an action. Different from previous approaches, our method does not require complex computation for graph matching or complex latent models to localize the parts. We model a video as a structured bag of trajectory groups...
Motion trajectory analysis is important for human motion recognition and human computer interaction. In this paper, we propose a flexible 3D trajectory indexing method for complex 3D motion recognition. Based on both point level and primitive-level descriptors, trajectories are represented in the sub-primitive level, the level between the point level and primitive level. Primitives are flexibly segmented...
The urban road traffic flow condition prediction is a fundamental issue in the intelligent transportation management system. While extracting the high-dimensional, nonlinear and random features of the transportation network is a challenge, which is very useful to improve the accuracy of traffic prediction. In this paper, we propose DeepSense, a novel deep temporal-spatial traffic flow feature learning...
The automation and motion control aspects of a developed multi-sensor measuring system are described in this contribution. The measuring system is designed to automatically detect and survey surface defects of microscopic size on macroscopic mechanical components. It is based on the hierarchical combination of optical sensors with different working ranges and resolutions. This measurement approach...
Android smart phone can be used in ITS (Intelligent Transportation Systems) to obtain people and vehicle’s location since it is integrated with GPS, direction sensor and acceleration sensor. Because the GPS built in smart phone always has an error of dozens of meters, improving the positioning accuracy is necessary before introducing it into ITS. This paper proposed an approach to improve the accuracy...
Brain-computer interface (BCI) is currently developed as an alternative technology with a potential to restore lost motor function in patients with neurological injuries. In this paper, we describe an integrated system of a non-invasive electroencephalogram (EEG)-based BCI with a non-invasive functional electrical stimulation (FES). This system enables the direct brain control of upper limbs to achieve...
To the trained-eye, experts can often identify a team based on their unique style of play due to their movement, passing and interactions. In this paper, we present a method which can accurately determine the identity of a team from spatiotemporal player tracking data. We do this by utilizing a formation descriptor which is found by minimizing the entropy of role-specific occupancy maps. We show how...
Access to accurate GSM power spectrograms in large cities can be of great interest to mobile network operators. Acquiring such information in urban settings is very challenging mainly due to the large area and high dynamics of environments. In this paper, we propose a novel scheme to tackle the large-scale mobile sensing problem. We first utilize an open source GSM project to collect RSSI values of...
This paper addresses the problem of human action detection/recognition by investigating interest points (IP) trajectory cues and by reducing undesirable small camera motion. We first detect speed up robust feature (SURF) to segment video into frame volume (FV) that contains small actions. This segmentation relies on IP trajectory tracking. Then, for each FV, we extract optical flow of every detected...
Based on new results on ideal adaptive sliding mode control (ASMC) design for nonlinear systems with uncertainties discussed in Part I of the present contribution, we extend the new designs to the real case in this paper (Part II) by using boundary layer method and filtered rate of the sliding variable. These modifications are proposed to enhance accuracy without overestimation of the uncertainty...
Roadside workers and emergency responders, such as police and emergency medical technicians, are at significant risk of being struck by vehicular traffic while performing their duties. While recent work has examined active and passive systems to reduce pedestrian collisions, current approaches require line of sight using either laser, infrared, or vision based systems. We address this problem by developing...
Map matching (MM), pins the drifting position data to the correct road link on which a vehicle is travelling, is a crucial step needed by many industrial or research ITS projects which rely on post-hoc analysis of trajectories. To address the unprecedented challenge of massive GPS data processing in urban transportation data center nowadays, this paper proposed an improved parallel topological map-matching...
Fluid mechanics considers two frames of reference for an observer watching a flow field: Eulerian and Lagrangian. The former is the frame of reference traditionally used for flow analysis, and involves extracting particle trajectories based on a vector field. With this work, we explore the opportunities that arise when considering these trajectories from the Lagrangian frame of reference. Specifically,...
This paper presents and investigates two new numerical algorithms (i.e., E47 algorithm and 94LVI algorithm) for solving the quadratic programming (QP) problem subject to inequality and bound constraints. Such a constrained QP problem is firstly converted equivalently into a linear variational inequality (LVI), and then converted equivalently into a piecewise-linear projection equation (PLPE). The...
A challenging problem that taxi service faces is to fulfill all passenger requests in different regions of a city and different time periods. Taxicab service rate of a region calculated from existing trajectory data can indicate the utilization rate of taxicabs in the region and help solving the problem. However, as trajectory data often contain corrupt or missing records in real scenarios, taxicab...
One of the fundamental problems in developmental robotics relates to the progressive spontaneous acquisition of motor abilities by an organism. Throughout this process, the speed of acquiring abilities, which we term ‘learnability’, is strongly limited by the dimensionality of the sensori-motor space; this in turn could affect the survival of an organism. In this paper, we tackle the problem of dimensional...
Cross-situational learning, the ability to learn word meanings across multiple scenes consisting of multiple words and referents, is thought to be an important tool for language acquisition. The ability has been studied in infants, children, and adults, and yet there is much debate about the basic storage and retrieval mechanisms that operate during cross-situational word learning. It has been difficult...
Recurrence plot is a useful analysis method for nonlinear time series, and has been widely used in studies of heart rate variability in recent years. In this paper, recurrence plot and corresponding quantification analysis were utilized to analyze the heart rate variability data from healthy people and congestive heart failure sufferers. It was found that the measures for standard recurrence quantification...
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