Person re-identification (re-id) is a critical problem in video analytics applications such as security and surveillance. The public release of several datasets and code for vision algorithms has ...facilitated rapid progress in this area over the last few years. However, directly comparing re-id algorithms reported in the literature has become difficult since a wide variety of features, experimental protocols, and evaluation metrics are employed. In order to address this need, we present an extensive review and performance evaluation of single- and multi-shot re-id algorithms. The experimental protocol incorporates the most recent advances in both feature extraction and metric learning. To ensure a fair comparison, all of the approaches were implemented using a unified code library that includes 11 feature extraction algorithms and 22 metric learning and ranking techniques. All approaches were evaluated using a new large-scale dataset that closely mimics a real-world problem setting, in addition to 16 other publicly available datasets: VIPeR, GRID, CAVIAR, DukeMTMC4ReID, 3DPeS, PRID, V47, WARD, SAIVT-SoftBio, CUHK01, CHUK02, CUHK03, RAiD, iLIDSVID, HDA+, and Market1501. The evaluation codebase and results will be made publicly available for community use.
Human re-identification across cameras with non-overlapping fields of view is one of the most important and difficult problems in video surveillance and analysis. However, current algorithms are ...likely to fail in real-world scenarios for several reasons. For example, surveillance cameras are typically mounted high above the ground plane, causing serious perspective changes. Also, most algorithms approach matching across images using the same descriptors, regardless of camera viewpoint or human pose. Here, we introduce a re-identification algorithm that addresses both problems. We build a model for human appearance as a function of pose, using training data gathered from a calibrated camera. We then apply this "pose prior" in online re-identification to make matching and identification more robust to viewpoint. We further integrate person-specific features learned over the course of tracking to improve the algorithm's performance. We evaluate the performance of the proposed algorithm and compare it to several state-of-the-art algorithms, demonstrating superior performance on standard benchmarking datasets as well as a challenging new airport surveillance scenario.
Functional connectivity has been demonstrated to be varying over time during sensory and cognitive processes. Quantitative examinations of such variations can significantly advance our understanding ...on large-scale functional organizations and their topological dynamics that support normal brain functional connectome and can be altered in individuals with brain disorders. However, toolboxes that integrate the complete functions for analyzing task-related brain functional connectivity, functional network topological properties, and their dynamics, are still lacking. The current study has developed a MATLAB toolbox, the Graph Theoretical Analysis of Task-Related Functional Dynamics (GAT-FD), which consists of four modules for sliding-window analyses, temporal mask generation, estimations of network properties and dynamics, and result display, respectively. All the involved functions have been tested and validated using functional magnetic resonance imaging data collected from human subjects when performing a block-designed task. The results demonstrated that the GAT-FD allows for effective and quantitative evaluations of the functional network properties and their dynamics during the task period. As an open-source and user-friendly package, the GAT-FD and its detailed user manual are freely available at https://www.nitrc.org/projects/gat_fd and https://centers.njit.edu/cnnl/gat_fd/.
Psychopathy is characterized by impulsivity, antisocial behavior, and deficient affect, and it has also been associated with attention deficits. However, studies of the relationship between ...psychopathy and the underlying neurophysiology of attention have yielded mixed results, which may be due to the heterogeneous nature of psychopathy as well as the failure to account for the influence of a history of traumatic brain injury (TBI). This study investigated whether the neurophysiology of attention is differentially associated with individual psychopathic traits, and whether a history of TBI may change these associations. Psychopathic traits were assessed among college students (age = 18–26 years; 63% male) with (
n
= 20) and without (
n
= 23) a history of mild TBI. Brain activation in bilateral middle frontal gyri (MFG) was measured with functional near-infrared spectroscopy (fNIRS) during a block-designed (rest and task blocks) visual sustained attention task. Relative to non-TBI controls, participants with a history of TBI showed significantly more activation in the right MFG in response to the task. In participants without a history of TBI, self-centered impulsivity was positively associated with activation in the right MFG during the rest blocks, while coldheartedness was negatively associated with activation in the left MFG during the task. No relationships between psychopathic traits and MFG activation were found in those with a history of TBI. These findings indicate that MFG hypoactivation and hyperactivation may contribute to the affective coldness and impulsivity of psychopathy, respectively, and highlight the importance of assessing TBI in psychopathy research.
With the proliferation of unmanned aerial vehicles (UAVs) in both commercial and military use, the public is paying increasing attention to UAV identification and regulation. The micro-Doppler ...characteristics of a UAV can reflect its structure and motion information, which provides an important reference for UAV recognition. The low flight altitude and small radar cross-section (RCS) of UAVs make the cancellation of strong ground clutter become a key problem in extracting the weak micro-Doppler signals. In this paper, a clutter suppression method based on an orthogonal matching pursuit (OMP) algorithm is proposed, which is used to process echo signals obtained by a linear frequency modulated continuous wave (LFMCW) radar. The focus of this method is on the idea of sparse representation, which establishes a complete set of environmental clutter dictionaries to effectively suppress clutter in the received echo signals of a hovering UAV. The processed signals are analyzed in the time–frequency domain. According to the flicker phenomenon of UAV rotor blades and related micro-Doppler characteristics, the feature parameters of unknown UAVs can be estimated. Compared with traditional signal processing methods, the method based on OMP algorithm shows advantages in having a low signal-to-noise ratio (−10 dB). Field experiments indicate that this approach can effectively reduce clutter power (−15 dB) and successfully extract micro-Doppler signals for identifying different UAVs.
MicroRNAs are involved in different cancer-related processes. MicroRNA-21 (miR-21), as an oncomiR, is overexpressed in all kinds of tumors and the role of miR-21 in carcinogenesis is elucidated in ...many cancers gradually. However, the function of miR-21 in osteosarcoma is still unclear. In our study, we found that miR-21 was significantly overexpressed in osteosarcoma tissues. More importantly, we confirmed that knockdown of miR-21 greatly decreased cell invasion and migration of MG-63. Furthermore, we identified that RECK (reversion-inducing-cysteine-rich protein with kazal motifs), a tumor suppressor gene, was a direct target of miR-21. Finally, the expression of RECK protein negatively correlated with the expression of miR-21 in human osteosarcoma tissues, indicating the potential regulation of RECK by miR-21. Our results suggest that miR-21 expression has a key role in regulating cellular processes in osteosarcoma, likely through regulating RECK and may serve as a therapeutic target.
Observational studies have identified associations between smoking, alcohol use, body mass index (BMI), and the levels of vitamin D with primary biliary cholangitis (PBC). However, there was a lack ...of randomization control studies to estimate the causal relationship. This study was to investigate the causal estimates for the effects of those risk factors on PBC.
The genetic instrument variants were extracted from genome-wide association studies in European ancestry. Two-sample mendelian randomization (MR) and multivariable mendelian randomization were used to determine genetically causal estimates. Primary analyses consisted of random-effects and fix-mode inverse-variance-weighted methods, followed by secondary sensitivity analyses to verify the results.
Our study showed that BMI was a causal factor for PBC (OR 1.35; 95% CI=1.03-1.77;
=0.029). In addition, we found that serum vitamin D levels had a protective effect on PBC after adjusting for BMI (OR 0.51; 95% CI=0.32-0.84;
=0.007). However, we failed to identify evidence supporting that genetic causal effect of smoking and alcohol intake were associated with PBC in European countries.
Our results enriched findings from previous epidemiology studies and provided evidence from MR that serum vitamin D concentrations and BMI were independent causal factors for PBC, suggesting that ensuing vitamin D sufficiency and healthy lifestyles might be a cost-effective measure for early intervention for PBC.
Keeping a Pan-Tilt-Zoom Camera Calibrated Ziyan Wu; Radke, R. J.
IEEE transactions on pattern analysis and machine intelligence,
08/2013, Letnik:
35, Številka:
8
Journal Article
Recenzirano
Pan-tilt-zoom (PTZ) cameras are pervasive in modern surveillance systems. However, we demonstrate that the (pan, tilt) coordinates reported by PTZ cameras become inaccurate after many hours of ...operation, endangering tracking and 3D localization algorithms that rely on the accuracy of such values. To solve this problem, we propose a complete model for a PTZ camera that explicitly reflects how focal length and lens distortion vary as a function of zoom scale. We show how the parameters of this model can be quickly and accurately estimated using a series of simple initialization steps followed by a nonlinear optimization. Our method requires only 10 images to achieve accurate calibration results. Next, we show how the calibration parameters can be maintained using a one-shot dynamic correction process; this ensures that the camera returns the same field of view every time the user requests a given (pan, tilt, zoom), even after hundreds of hours of operation. The dynamic calibration algorithm is based on matching the current image against a stored feature library created at the time the PTZ camera is mounted. We evaluate the calibration and dynamic correction algorithms on both experimental and real-world datasets, demonstrating the effectiveness of the techniques.
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