227 resultados para Tracker
Resumo:
The necessity of installing a forward tracking detector stack is discussed for the Hadron Physics LanzhoU Spectrometer(HPLUS). A local tracker is developed to solve the multi-track finding problem. The track candidates are searched iteratively via Hough Transform. The fake tracks are removed by a least square fitting process. With this tracker we have studied the feasibility of pp -> pp + phi(-> K+K-), a typical physical channel proposed on HPLUS. The single track momentum resolution due to the uncertainty of the positioning in FTD is 1.3%. The multiple scattering effect contributes about 20% to the momentum resolution in the FTD coverage. The width and the signal-to-background ratio of the reconstructed phi are 1.51 MeV and 4.36, respectively, taking into account the direct Kaon channel pp -> pp + K+K- as background. The geometry coverage of FTD for phi events is about 85.4%. Based on the current fast simulation and estimation, the geometrical configuration of FTD meets the physical requirement of HPLUS under the current luminosity and multiplicity conditions. The tracker is applicable in the full simulation coming next and is extendable to other tracking component of HPLUS.
Resumo:
We present the results of an elliptic flow, v(2), analysis of Cu + Cu collisions recorded with the solenoidal tracker detector (STAR) at the BNL Relativistic Heavy Ion Collider at root s(NN) = 62.4 and 200 GeV. Elliptic flow as a function of transverse momentum, v(2)(p(T)), is reported for different collision centralities for charged hadrons h(+/-) and strangeness-ontaining hadrons K-S(0), Lambda, Xi, and phi in the midrapidity region vertical bar eta vertical bar < 1.0. Significant reduction in systematic uncertainty of the measurement due to nonflow effects has been achieved by correlating particles at midrapidity, vertical bar eta vertical bar < 1.0, with those at forward rapidity, 2.5 < vertical bar eta vertical bar < 4.0. We also present azimuthal correlations in p + p collisions at root s = 200 GeV to help in estimating nonflow effects. To study the system-size dependence of elliptic flow, we present a detailed comparison with previously published results from Au + Au collisions at root s(NN) = 200 GeV. We observe that v(2)(p(T)) of strange hadrons has similar scaling properties as were first observed in Au + Au collisions, that is, (i) at low transverse momenta, p(T) < 2 GeV/c, v(2) scales with transverse kinetic energy, m(T) - m, and (ii) at intermediate p(T), 2 < p(T) < 4 GeV/c, it scales with the number of constituent quarks, n(q.) We have found that ideal hydrodynamic calculations fail to reproduce the centrality dependence of v(2)(p(T)) for K-S(0) and Lambda. Eccentricity scaled v(2) values, v(2)/epsilon, are larger in more central collisions, suggesting stronger collective flow develops in more central collisions. The comparison with Au + Au collisions, which go further in density, shows that v(2)/epsilon depends on the system size, that is, the number of participants N-part. This indicates that the ideal hydrodynamic limit is not reached in Cu + Cu collisions, presumably because the assumption of thermalization is not attained.
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We present the first measurements of identified hadron production, azimuthal anisotropy, and pion interferometry from Au + Au collisions below the nominal injection energy at the BNL Relativistic Heavy-Ion Collider (RHIC) facility. The data were collected using the large acceptance solenoidal tracker at RHIC (STAR) detector at root s(NN) = 9.2 GeV from a test run of the collider in the year 2008. Midrapidity results on multiplicity density dN/dy in rapidity y, average transverse momentum < p(T)>, particle ratios, elliptic flow, and Hanbury-Brown-Twiss (HBT) radii are consistent with the corresponding results at similar root s(NN) from fixed-target experiments. Directed flow measurements are presented for both midrapidity and forward-rapidity regions. Furthermore the collision centrality dependence of identified particle dN/dy, < p(T)>, and particle ratios are discussed. These results also demonstrate that the capabilities of the STAR detector, although optimized for root s(NN) = 200 GeV, are suitable for the proposed QCD critical-point search and exploration of the QCD phase diagram at RHIC.
Resumo:
本文介绍了一个用于实际的电视精密跟踪控制系统,该控制系统在外场跟踪飞行体时稳定可靠,跟踪精度为数角秒.文中论述了人参与的复合捕获控制系统,找到了该系统参数的设计准则,即在切换时要满足相对变化量Δ≤15%.其次,重点论述了三阶无静差电视精密跟踪控制系统的设计方法,即利用 Z 变换直接求解,使得系统满足最佳条件旬(?)_(max)/(?)K_i=0和(?)_(max)/(?)K_f~2>0,从而,使得该控制系统满足了高稳定度和高精度的技术指标,并在实际中获得了应用.
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The utility of vision-based face tracking for dual pointing tasks is evaluated. We first describe a 3-D face tracking technique based on real-time parametric motion-stereo, which is non-invasive, robust, and self-initialized. The tracker provides a real-time estimate of a ?frontal face ray? whose intersection with the display surface plane is used as a second stream of input for scrolling or pointing, in paral-lel with hand input. We evaluated the performance of com-bined head/hand input on a box selection and coloring task: users selected boxes with one pointer and colors with a second pointer, or performed both tasks with a single pointer. We found that performance with head and one hand was intermediate between single hand performance and dual hand performance. Our results are consistent with previously reported dual hand conflict in symmetric pointing tasks, and suggest that a head-based input stream should be used for asymmetric control.
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Location is a primary cue in many context-aware computing systems, and is often represented as a global coordinate, room number, or Euclidean distance various landmarks. A user?s concept of location, however, is often defined in terms of regions in which common activities occur. We show how to partition a space into such regions based on patterns of observed user location and motion. These regions, which we call activity zones, represent regions of similar user activity, and can be used to trigger application actions, retrieve information based on previous context, and present information to users. We suggest that context-aware applications can benefit from a location representation learned from observing users. We describe an implementation of our system and present two example applications whose behavior is controlled by users? entry, exit, and presence in the zones.
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An automated system for detection of head movements is described. The goal is to label relevant head gestures in video of American Sign Language (ASL) communication. In the system, a 3D head tracker recovers head rotation and translation parameters from monocular video. Relevant head gestures are then detected by analyzing the length and frequency of the motion signal's peaks and valleys. Each parameter is analyzed independently, due to the fact that a number of relevant head movements in ASL are associated with major changes around one rotational axis. No explicit training of the system is necessary. Currently, the system can detect "head shakes." In experimental evaluation, classification performance is compared against ground-truth labels obtained from ASL linguists. Initial results are promising, as the system matches the linguists' labels in a significant number of cases.
Resumo:
We propose a multi-object multi-camera framework for tracking large numbers of tightly-spaced objects that rapidly move in three dimensions. We formulate the problem of finding correspondences across multiple views as a multidimensional assignment problem and use a greedy randomized adaptive search procedure to solve this NP-hard problem efficiently. To account for occlusions, we relax the one-to-one constraint that one measurement corresponds to one object and iteratively solve the relaxed assignment problem. After correspondences are established, object trajectories are estimated by stereoscopic reconstruction using an epipolar-neighborhood search. We embedded our method into a tracker-to-tracker multi-view fusion system that not only obtains the three-dimensional trajectories of closely-moving objects but also accurately settles track uncertainties that could not be resolved from single views due to occlusion. We conducted experiments to validate our greedy assignment procedure and our technique to recover from occlusions. We successfully track hundreds of flying bats and provide an analysis of their group behavior based on 150 reconstructed 3D trajectories.
Resumo:
We introduce Active Hidden Models (AHM) that utilize kernel methods traditionally associated with classification. We use AHMs to track deformable objects in video sequences by leveraging kernel projections. We introduce the "subset projection" method which improves the efficiency of our tracking approach by a factor of ten. We successfully tested our method on facial tracking with extreme head movements (including full 180-degree head rotation), facial expressions, and deformable objects. Given a kernel and a set of training observations, we derive unbiased estimates of the accuracy of the AHM tracker. Kernels are generally used in classification methods to make training data linearly separable. We prove that the optimal (minimum variance) tracking kernels are those that make the training observations linearly dependent.
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We present a multimodal detection and tracking algorithm for sensors composed of a camera mounted between two microphones. Target localization is performed on color-based change detection in the video modality and on time difference of arrival (TDOA) estimation between the two microphones in the audio modality. The TDOA is computed by multiband generalized cross correlation (GCC) analysis. The estimated directions of arrival are then postprocessed using a Riccati Kalman filter. The visual and audio estimates are finally integrated, at the likelihood level, into a particle filter (PF) that uses a zero-order motion model, and a weighted probabilistic data association (WPDA) scheme. We demonstrate that the Kalman filtering (KF) improves the accuracy of the audio source localization and that the WPDA helps to enhance the tracking performance of sensor fusion in reverberant scenarios. The combination of multiband GCC, KF, and WPDA within the particle filtering framework improves the performance of the algorithm in noisy scenarios. We also show how the proposed audiovisual tracker summarizes the observed scene by generating metadata that can be transmitted to other network nodes instead of transmitting the raw images and can be used for very low bit rate communication. Moreover, the generated metadata can also be used to detect and monitor events of interest.
Resumo:
In this paper, we present an inertial-sensor-based monitoring system for measuring the movement of human upper limbs. Two wearable inertial sensors are placed near the wrist and elbow joints, respectively. The measurement drift in segment orientation is dramatically reduced after a Kalman filter is applied to estimate inclinations using accelerations and turning rates from gyroscopes. Using premeasured lengths of the upper and lower arms, we compute the position of the wrist and elbow joints via a proposed kinematic model. Experimental results demonstrate that this new motion capture system, in comparison to an optical motion tracker, possesses an RMS position error of less than 0.009 m, with a drift of less than 0.005 ms-1 in five daily activities. In addition, the RMS angle error is less than 3??. This indicates that the proposed approach has performed well in terms of accuracy and reliability.
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The goal of this study is to identify cues for the cognitive process of attention in ancient Greek art, aiming to find confirmation of its possible use by ancient Greek audiences and artists. Evidence of cues that trigger attention’s psychological dispositions was searched through content analysis of image reproductions of ancient Greek sculpture and fine vase painting from the archaic to the Hellenistic period - ca. 7th -1st cent. BC. Through this analysis, it was possible to observe the presence of cues that trigger orientation to the work of art (i.e. amplification, contrast, emotional salience, simplification, symmetry), of a cue that triggers a disseminate attention to the parts of the work (i.e. distribution of elements) and of cues that activate selective attention to specific elements in the work of art (i.e. contrast of elements, salient color, central positioning of elements, composition regarding the flow of elements and significant objects). Results support the universality of those dispositions, probably connected with basic competencies that are hard-wired in the nervous system and in the cognitive processes.
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We present a Spatio-temporal 2D Models Framework (STMF) for 2D-Pose tracking. Space and time are discretized and a mixture of probabilistic "local models" is learnt associating 2D Shapes and 2D Stick Figures. Those spatio-temporal models generalize well for a particular viewpoint and state of the tracked action but some spatio-temporal discontinuities can appear along a sequence, as a direct consequence of the discretization. To overcome the problem, we propose to apply a Rao-Blackwellized Particle Filter (RBPF) in the 2D-Pose eigenspace, thus interpolating unseen data between view-based clusters. The fitness to the images of the predicted 2D-Poses is evaluated combining our STMF with spatio-temporal constraints. A robust, fast and smooth human motion tracker is obtained by tracking only the few most important dimensions of the state space and by refining deterministically with our STMF.
Resumo:
In this paper, we consider the problem of tracking similar objects. We show how a mean field approach can be used to deal with interacting targets and we compare it with Markov Chain Monte Carlo (MCMC). Two mean field implementations are presented. The first one is more general and uses particle filtering. We discuss some simplifications of the base algorithm that reduce the computation time. The second one is based on suitable Gaussian approximations of probability densities that lead to a set of self-consistent equations for the means and covariances. These equations give the Kalman solution if there is no interaction. Experiments have been performed on two kinds of sequences. The first kind is composed of a single long sequence of twenty roaming ants and was previously analysed using MCMC. In this case, our mean field algorithms obtain substantially better results. The second kind corresponds to selected sequences of a football match in which the interaction avoids tracker coalescence in situations where independent trackers fail.
Resumo:
The application of Eye Tracking (ET) to the study of social functioning in Asperger Syndrome (AS) provides a unique perspective into social attention and cognition in this atypical neurodevelopmental group. Research in this area has shown how ET can capture social attention atypicalities within this group, such as diminished fixations to the eye region when viewing still images and movie clips; increased fixation to the mouth region; reduced face gaze. Issues exist, however, within the literature, where the type (static/dynamic) and the content (ecological validity) of stimuli used appear to affect the nature of the gaze patterns reported. Objectives: Our research aims were: using the same group of adolescents with AS, to compare their viewing patterns to age and IQ matched typically developing (TD) adolescents using stimuli considered to represent a hierarchy of ecological validity, building from static facial images; through a non-verbal movie clip; through verbal footage from real-life conversation; to eye tracking during real-life conversation. Methods: Eleven participants with AS were compared to 11 TD adolescents, matched for age and IQ. In Study 1, participants were shown 2 sets of static facial images (emotion faces, still images taken from the dynamic clips). In Study 2, three dynamic clips were presented (1 non-verbal movie clip, 2 verbal footage from real-life conversation). Study 3 was an exploratory study of eye tracking during a real-life conversation. Eye movements were recorded via a HiSpeeed (240Hz) SMI eye tracker fitted with chin and forehead rests. Various methods of analysis were used, including a paradigm for temporal analysis of the eye movement data. Results: Results from these studies confirmed that the atypical nature of social attention in AS was successfully captured by this paradigm. While results differed across stimulus sets,
collectively they demonstrated how individuals with AS failed to focus on the most socially relevant aspects of the various stimuli presented. There was also evidence that the eye movements of the AS group were atypically affected by the presence of motion and verbal information. Discriminant Function Analysis demonstrated that the ecological validity of stimuli was an important factor in identifying atypicalities associated with AS, with more accurate classifications of AS and TD groups occurring for more naturalistic stimuli (dynamic rather than static). Graphical analysis of temporal sequences of eye movements revealed the atypical manner in which AS participants followed interactions within the dynamic stimuli. Taken together with data on the order of gaze patterns, more subtle atypicalities were detected in the gaze behaviour of AS individuals towards more socially pertinent regions of the dynamic stimuli. Conclusions: These results have potentially important implications for our understanding of deficits in Asperger Syndrome, as they show that, with more naturalistic stimuli, subtle differences in social attention can be detected that