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Digital door lock system is a widely used physical security system. It restricts unauthorized accesses and protects assets or private spaces. However, once its password has been exposed to unauthorized people, it becomes useless. In this paper, we propose a novel side channel attack model, which enables a cracking of a digital door lock password. We noted that when people press the key-lock button,...
Laser rangefinders are very popular sensors in robot localization due to their accuracy. Typically, localization algorithms based on these sensors compare range measurements with previously obtained maps of the environment. As many indoor environments are highly symmetrical (e.g., most rooms have the same layout and most corridors are very similar) these systems may fail to recognize one location...
We consider the problem of online robotic sampling in environmental monitoring tasks where the goal is to collect k best samples from n sequentially occurring measurements. In contrast to many existing works that seek to maximize the utility of the selected samples online, we aim to find the cardinality constrained subset of streaming measurements under irrevocable sampling decisions so that the prediction...
For manifolds with topologies that strongly differ from the standard topology of Rn, using common filters created for linear domains can yield misleading results. While there is a lot of ongoing research on estimation on the unit circle, higher-dimensional problems particularly pose a challenge. One important generalization of the unit circle is the unit hypersphere. In this paper, we propose a recursive...
In this paper, we introduce a new hardware platform that mimics a compound eye of an insect and propose an algorithm to detect objects using it. The compound eye camera has a wide viewing angle and simulates a number of single eyes on its hemisphere. Each single eye is an elementary unit to acquire visual inputs. Visual information from single eyes is hierarchically merged to estimate objectness....
In monocular vision systems, lack of knowledge about metric distances caused by the inherent scale ambiguity can be a strong limitation for some applications. We offer a method for fusing inertial measurements with monocular odometry or tracking to estimate metric distances in inertial-monocular systems and to increase the rate of pose estimates. As we performed the fusion in a loosely-coupled manner,...
In this work, we propose a novel human activity recognition method from depth videos using robust spatiotemporal features with convolutional neural network. From the depth images of activities, human body parts are segmented based on random features on a random forest. From the segmented body parts in a depth image of an activity video, spatial features are extracted such as angles of the 3-D body...
This paper introduces a multi-Bayesian framework for detection and classification of features in environments abundant with error-inducing noise. This approach takes advantage of Bayesian correction and classification in three distinct stages. The corrective scheme described here extracts useful but highly stochastic features from a data source, whether vision-based or otherwise, to aid in higher-level...
Gait recognition plays a very vital role in many practical applications of computer and robot vision in smart environments such as health care for elderly using smart home technology. Hence, it has been attracting considerable attentions from many machine vision researchers in last decades. In this paper, we propose a novel method for depth video-based gait recognition using robust features and deep...
In the present day, industry has been brought closer to the Industry 4.0 paradigm due to its needs of reaching better industrial communications and improving the control process. According to the IIoT concepts, Cyber Physical Production Systems (CPPS) are normally connected to each other, and also connected to the virtual world of global digital networks. By introducing the IEC-61499 standard, CPPS...
In this paper, a study has been conducted to present a high resolution optical localization and tracking method for micro-robots or micro-conveyors moved over a smart surface in a context of micro-factory. The first approach of this work is presented here, the localization and tracking principles are described, the algorithm is presented and finally, experimentation work on system calibration and...
In recent years, a great many robot-assisted therapy systems have been developed and applied in neural rehabilitation. In this paper, we develop a wearable upper limb exoskeleton robot for the purpose of assisting the disable patients to execute effective rehabilitation. The proposed exoskeleton system consists of 7 degrees of freedom (DOFs) and is capable of providing naturalistic assistance of shoulder,...
In this paper, the problem of the exploration of an unknown environment by deploying a fleet of Micro-Aerial Vehicles (MAV) is considered. As a single robot has already proven its efficiency for this task, the challenge is to extend it to a multi-robots system to reduce the exploration time. For this purpose, a cooperative navigation strategy is proposed based on a specific utility function and inter-robots...
Functional near-infrared spectroscopy (fNIRS) can be employed to investigate brain activation by measuring the absorption of near-infrared light through an intact skull. fNIRS can measure hemoglobin signals, which are similar to functional magnetic resonance imaging (fMRI) blood-oxygen-level-dependent (BOLD) signals. The general linear model (GLM), which is a standard method for fMRI imaging, has...
As the world's aging population grows, fall is becoming a major problem in public health. It is one of the most vital risk to the elderly. Many technology based fall detection systems have been developed in recent years with hardware ranging from wearable devices to ambience sensors and video cameras. Several machine learning based fall detection classifiers have been developed to process sensor data...
A new multiple classifier system (MCS) is proposed based on CTSP (classification based on Testing Sample Pairs), which is a kind of applicable and efficient classification method. However, the original output form of the CTSP is only crisp class labels. To make use of the information provided by the classifier, in this paper, the output of CTSP is modeled using the membership function. Then, the fuzzy-cautious...
Robotic ground vehicles are commonly used in various road conditions for performing special tasks with different levels of autonomy. This requires the robots to possess a certain degree of perception about the road conditions up ahead and make plans accordingly. It is essential for the robots to be able to quickly adapt their perception for various road conditions they operate. In this paper, an adaptive...
This paper presents a fusion of monocular camera-based metric localization, IMU and odometry in dynamic environments of public roads. We build multiple vision-based maps and use them at the same time in localization phase. For the mapping phase, visual maps are built by employing ORB-SLAM and accurate metric positioning from LiDAR-based NDT scan matching. This external positioning is utilized to correct...
This paper presents a grid-based indoor radiolocation technique based on a Spatially Coherent Path Loss Model (SCPL). Received Signal Strength (RSS) fingerprints are collected at different positions in the environment from which the radio wave propagation for the environment is empirically approximated with the SCPL model. Unlike the conventional path loss models, SCPL approximates radio wave propagation...
In this paper, we present an approach to Multi-Object Tracking (MOT) that is based on the Ensemble Kalman Filter (EnKF). The EnKF is a standard algorithm for data assimilation in high-dimensional state spaces that is mainly used in geosciences, but has so far only attracted little attention for object tracking problems. In our approach, the Optimal Subpattern Assignment (OSPA) distance is used for...
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