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Robotic mapping: A survey
- EXPLORING ARTIFICIAL INTELLIGENCE IN THE NEW MILLENIUM
, 2002
"... This article provides a comprehensive introduction into the field of robotic mapping, with a focus on indoor mapping. It describes and compares various probabilistic techniques, as they are presently being applied to a vast array of mobile robot mapping problems. The history of robotic mapping is al ..."
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Cited by 367 (6 self)
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This article provides a comprehensive introduction into the field of robotic mapping, with a focus on indoor mapping. It describes and compares various probabilistic techniques, as they are presently being applied to a vast array of mobile robot mapping problems. The history of robotic mapping is also described, along with an extensive list of open research problems.
Online Boosting and Vision
, 2006
"... Boosting has become very popular in computer vision, showing impressive performance in detection and recognition tasks. Mainly off-line training methods have been used, which implies that all training data has to be a priori given; training and usage of the classifier are separate steps. Training th ..."
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Cited by 246 (41 self)
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Boosting has become very popular in computer vision, showing impressive performance in detection and recognition tasks. Mainly off-line training methods have been used, which implies that all training data has to be a priori given; training and usage of the classifier are separate steps. Training the classifier on-line and incrementally as new data becomes available has several advantages and opens new areas of application for boosting in computer vision. In this paper we propose a novel on-line AdaBoost feature selection method. In conjunction with efficient feature extraction methods the method is real time capable. We demonstrate the multifariousness of the method on such diverse tasks as learning complex background models, visual tracking and object detection. All approaches benefit significantly by the on-line training. 1.
Gesture recognition: A survey
- IEEE TRANSACTIONS ON SYSTEMS, MAN AND CYBERNETICS - PART C
, 2007
"... Gesture recognition pertains to recognizing meaningful expressions of motion by a human, involving the hands, arms, face, head, and/or body. It is of utmost importance in designing an intelligent and efficient human–computer interface. The applications of gesture recognition are manifold, ranging fr ..."
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Cited by 197 (0 self)
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Gesture recognition pertains to recognizing meaningful expressions of motion by a human, involving the hands, arms, face, head, and/or body. It is of utmost importance in designing an intelligent and efficient human–computer interface. The applications of gesture recognition are manifold, ranging from sign language through medical rehabilitation to virtual reality. In this paper, we provide a survey on gesture recognition with particular emphasis on hand gestures and facial expressions. Applications involving hidden Markov models, particle filtering and condensation, finite-state machines, optical flow, skin color, and connectionist models are discussed in detail. Existing challenges and future research possibilities are also highlighted.
Monitoring and Early Warning for Internet Worms
- In Proceedings of 10th ACM Conference on Computer and Communications Security (CCS’03
, 2003
"... After the Code Red incident in 2001 and the SQL Slammer in January 2003, it is clear that a simple self-propagating worm can quickly spread across the Internet, infects most vulnerable computers before people can take e#ective countermeasures. The fast spreading nature of worms calls for a worm moni ..."
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Cited by 179 (18 self)
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After the Code Red incident in 2001 and the SQL Slammer in January 2003, it is clear that a simple self-propagating worm can quickly spread across the Internet, infects most vulnerable computers before people can take e#ective countermeasures. The fast spreading nature of worms calls for a worm monitoring and early warning system. In this paper, we propose e#ective algorithms for early detection of the presence of a worm and the corresponding monitoring system. Based on epidemic model and observation data from the monitoring system, by using the idea of "detecting the trend, not the rate" of monitored illegitimated scan tra#c, we propose to use a Kalman filter to detect a worm's propagation at its early stage in real-time. In addition, we can effectively predict the overall vulnerable population size, and correct the bias in the observed number of infected hosts. Our simulation experiments for Code Red and SQL Slammer show that with observation data from a small fraction of IP addresses, we can detect the presence of a worm when it infects only 1% to 2% of the vulnerable computers on the Internet.
SCAAT: Incremental Tracking with Incomplete Information
, 1997
"... We present a promising new mathematical method for tracking a user's pose (position and orientation) for interactive computer graphics. The method, which is applicable to a wide variety of both commercial and experimental systems, improves accuracy by properly assimilating sequential observatio ..."
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Cited by 160 (14 self)
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We present a promising new mathematical method for tracking a user's pose (position and orientation) for interactive computer graphics. The method, which is applicable to a wide variety of both commercial and experimental systems, improves accuracy by properly assimilating sequential observations, filtering sensor measurements, and by concurrently autocalibrating source and sensor devices. It facilitates user motion prediction, multisensor data fusion, and higher report rates with lower latency than previous methods. Tracking systems determine the user's pose by measuring signals from low-level hardware sensors. For reasons of physics and economics, most systems make multiple sequential measurements which are then combined to produce a single tracker report. For example, commercial magnetic trackers using the SPASYN ( Space Synchro) system sequentially measure three magnetic vectors and then combine them mathematically to produce a report of the sensor pose. Our new approach produces tracker reports as each new lowlevel sensor measurement is made rather than waiting to form a complete collection of observations. Because single observations under-constrain the mathematical solution, we refer to our approach as single-constraint-at-a-time or SCAAT tracking. The key is that the single observations provide some information about the user's state, and thus can be used to incrementally improve a previous estimate. We recursively apply this principle, incorporating new sensor data as soon as it is measured. With this approach we are able to generate estimates more frequently, with less latency, and with improved accuracy. We present results from both an actual implementation, and from extensive simulations.
Adapting the Sample Size in Particle Filters Through KLD-Sampling
- International Journal of Robotics Research
, 2003
"... Over the last years, particle filters have been applied with great success to a variety of state estimation problems. In this paper we present a statistical approach to increasing the efficiency of particle filters by adapting the size of sample sets during the estimation process. ..."
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Cited by 150 (9 self)
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Over the last years, particle filters have been applied with great success to a variety of state estimation problems. In this paper we present a statistical approach to increasing the efficiency of particle filters by adapting the size of sample sets during the estimation process.
Monocular model-based 3d tracking of rigid objects: A survey
- In Foundations and Trends in Computer Graphics and Vision
, 2005
"... Many applications require tracking of complex 3D objects. These include visual servoing of robotic arms on specific target objects, Aug-mented Reality systems that require real-time registration of the object to be augmented, and head tracking systems that sophisticated inter-faces can use. Computer ..."
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Cited by 143 (4 self)
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Many applications require tracking of complex 3D objects. These include visual servoing of robotic arms on specific target objects, Aug-mented Reality systems that require real-time registration of the object to be augmented, and head tracking systems that sophisticated inter-faces can use. Computer Vision offers solutions that are cheap, practical and non-invasive. This survey reviews the different techniques and approaches that have been developed by industry and research. First, important math-ematical tools are introduced: Camera representation, robust estima-tion and uncertainty estimation. Then a comprehensive study is given of the numerous approaches developed by the Augmented Reality and Robotics communities, beginning with those that are based on point or planar fiducial marks and moving on to those that avoid the need to engineer the environment by relying on natural features such as edges, texture or interest. Recent advances that avoid manual initialization and failures due to fast motion are also presented. The survery con-cludes with the different possible choices that should be made when implementing a 3D tracking system and a discussion of the future of vision-based 3D tracking. Because it encompasses many computer vision techniques from low-level vision to 3D geometry and includes a comprehensive study of the massive literature on the subject, this survey should be the handbook of the student, the researcher, or the engineer who wants to implement a 3D tracking system. 1
Computer Puppetry: An Importance-Based Approach
- ACM Transactions on Graphics
, 2001
"... this article, we provide a comprehensive solution to the problem of transferring the observations of the motion capture sensors to an animated character whose size and proportion may be different from the performer's. Our goal is to map as many of the important aspects of the motion to the targ ..."
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Cited by 99 (6 self)
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this article, we provide a comprehensive solution to the problem of transferring the observations of the motion capture sensors to an animated character whose size and proportion may be different from the performer's. Our goal is to map as many of the important aspects of the motion to the target character as possible, while meeting the online, real-time demands of computer puppetry. We adopt a Kalman filter scheme that addresses motion capture noise issues in this setting. We provide the notion of dynamic importance of an end-effector that allows us to determine what aspects of the performance must be kept in the resulting motion. We introduce a novel inverse kinematics solver that realizes these important aspects within tight real-time constraints. Our approach is demonstrated by its application to broadcast television performances
Survey on pedestrian detection for advanced driver assistance systems
- IEEE PAMI, available online: http://doi.ieeecomputersociety.org/10.1109/TPAMI.2009.122
, 2009
"... Abstract—Advanced driver assistance systems (ADASs), and particularly pedestrian protection systems (PPSs), have become an active research area aimed at improving traffic safety. The major challenge of PPSs is the development of reliable on-board pedestrian detection systems. Due to the varying appe ..."
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Cited by 89 (4 self)
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Abstract—Advanced driver assistance systems (ADASs), and particularly pedestrian protection systems (PPSs), have become an active research area aimed at improving traffic safety. The major challenge of PPSs is the development of reliable on-board pedestrian detection systems. Due to the varying appearance of pedestrians (e.g., different clothes, changing size, aspect ratio, and dynamic shape) and the unstructured environment, it is very difficult to cope with the demanded robustness of this kind of system. Two problems arising in this research area are the lack of public benchmarks and the difficulty in reproducing many of the proposed methods, which makes it difficult to compare the approaches. As a result, surveying the literature by enumerating the proposals one-after-another is not the most useful way to provide a comparative point of view. Accordingly, we present a more convenient strategy to survey the different approaches. We divide the problem of detecting pedestrians from images into different processing steps, each with attached responsibilities. Then, the different proposed methods are analyzed and classified with respect to each processing stage, favoring a comparative viewpoint. Finally, discussion of the important topics is presented, putting special emphasis on the future needs and challenges. Index Terms—ADAS, pedestrian detection, on-board vision, survey. Ç 1
Bayesian Population Decoding of Motor Cortical Activity Using a Kalman Filter
, 2006
"... Effective neural motor prostheses require a method for decoding neural activity representing desired movement. In particular, the accurate reconstruction of a continuous motion signal is necessary for the control of devices such as computer cursors, robots, or a patient’s own paralyzed limbs. For su ..."
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Cited by 82 (12 self)
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Effective neural motor prostheses require a method for decoding neural activity representing desired movement. In particular, the accurate reconstruction of a continuous motion signal is necessary for the control of devices such as computer cursors, robots, or a patient’s own paralyzed limbs. For such applications, we developed a real-time system that uses Bayesian inference techniques to estimate hand motion from the firing rates of multiple neurons. In this study, we used recordings that were previously made in the arm area of primary motor cortex in awake behaving monkeys using a chronically implanted multielectrode microarray. Bayesian inference involves computing the posterior probability of the hand motion conditioned on a sequence of observed firing rates; this is formulated in terms of the product of a likelihood and a prior. The likelihood term models the probability of firing rates given a particular hand motion. We found that a linear gaussian model could be used to approximate this likelihood and could be readily learned from a small amount
