3,260 research outputs found
Review of Person Re-identification Techniques
Person re-identification across different surveillance cameras with disjoint
fields of view has become one of the most interesting and challenging subjects
in the area of intelligent video surveillance. Although several methods have
been developed and proposed, certain limitations and unresolved issues remain.
In all of the existing re-identification approaches, feature vectors are
extracted from segmented still images or video frames. Different similarity or
dissimilarity measures have been applied to these vectors. Some methods have
used simple constant metrics, whereas others have utilised models to obtain
optimised metrics. Some have created models based on local colour or texture
information, and others have built models based on the gait of people. In
general, the main objective of all these approaches is to achieve a
higher-accuracy rate and lowercomputational costs. This study summarises
several developments in recent literature and discusses the various available
methods used in person re-identification. Specifically, their advantages and
disadvantages are mentioned and compared.Comment: Published 201
Impaired perception of biological motion in Parkinson’s disease
OBJECTIVE: We examined biological motion perception in Parkinson’s disease (PD). Biological motion perception is related to one’s own motor function and depends on the integrity of brain areas affected in PD, including posterior superior temporal sulcus. If deficits in biological motion perception exist, they may be specific to perceiving natural/fast walking patterns that individuals with PD can no longer perform, and may correlate with disease-related motor dysfunction. METHOD: Twenty-six nondemented individuals with PD and 24 control participants viewed videos of point-light walkers and scrambled versions that served as foils, and indicated whether each video depicted a human walking. Point-light walkers varied by gait type (natural, parkinsonian) and speed (0.5, 1.0, 1.5 m/s). Participants also completed control tasks (object motion, coherent motion perception), a contrast sensitivity assessment, and a walking assessment. RESULTS: The PD group demonstrated significantly less sensitivity to biological motion than the control group (p < .001, Cohen’s d = 1.22), regardless of stimulus gait type or speed, with a less substantial deficit in object motion perception (p = .02, Cohen’s d = .68). There was no group difference in coherent motion perception. Although individuals with PD had slower walking speed and shorter stride length than control participants, gait parameters did not correlate with biological motion perception. Contrast sensitivity and coherent motion perception also did not correlate with biological motion perception. CONCLUSION: PD leads to a deficit in perceiving biological motion, which is independent of gait dysfunction and low-level vision changes, and may therefore arise from difficulty perceptually integrating form and motion cues in posterior superior temporal sulcus.Published versio
Microsoft Kinect-based differences in lower limb kinematics and temporal characteristics of sit to walking phase of modified TUG test between men with and without Parkinson's disease
http://www.ester.ee/record=b476770
Extraction of bodily features for gait recognition and gait attractiveness evaluation
This is the author's accepted manuscript. The final publication is available at Springer via
http://dx.doi.org/10.1007/s11042-012-1319-2. Copyright @ 2012 Springer.Although there has been much previous research on which bodily features are most important in gait analysis, the questions of which features should be extracted from gait, and why these features in particular should be extracted, have not been convincingly answered. The primary goal of the study reported here was to take an analytical approach to answering these questions, in the context of identifying the features that are most important for gait recognition and gait attractiveness evaluation. Using precise 3D gait motion data obtained from motion capture, we analyzed the relative motions from different body segments to a root marker (located on the lower back) of 30 males by the fixed root method, and compared them with the original motions without fixing root. Some particular features were obtained by principal component analysis (PCA). The left lower arm, lower legs and hips were identified as important features for gait recognition. For gait attractiveness evaluation, the lower legs were recognized as important features.Dorothy Hodgkin Postgraduate Award and HEFCE
Evaluation of CNN architectures for gait recognition based on optical flow maps
This work targets people identification in video based on the way they walk (\ie gait) by using deep learning architectures. We explore the use of convolutional neural networks (CNN) for learning high-level descriptors from low-level motion features (\ie optical flow components). The low number of training samples for each subject and the use of a test set containing subjects different from the training ones makes the search of a good CNN architecture a challenging task.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec
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