3dhumanmotionanalysis from a single viewpoint is an extremely challenge computer vision task due to the lack of depth information and complex human movements. To resolve these problems, based on the quantum comput...
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ISBN:
(纸本)9781509038237;9781509038220
3dhumanmotionanalysis from a single viewpoint is an extremely challenge computer vision task due to the lack of depth information and complex human movements. To resolve these problems, based on the quantum computing and immune clonal operator, a novel evolution algorithm, called a quantumbehaved clonal algorithm(QBCA), is proposed for 3dhumanmotionanalysis. Firstly, a 2 d part-basedhumandetector(PBd) is used to compute the 2 d landmarks of key body joints. Then, humanmotionanalysis is performed by optimizing a distance similarity function between the detected 2 d landmarks and 2 d projection of predicted3d joint points using QBCA. Moreover, our method not only has a good balance between exploitation and exploration, but also searches both local optimum solution and global optimum solution, simultaneously. Extensive results on PARSE andhuman Eva dataset demonstrate the robustness and effectiveness of our proposed method.
Falls on the stairs are a common cause of accidental injury among the older adults. Understanding the mechanisms leading to such accidents may improve not only the prevention of falls, but also support independent liv...
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ISBN:
(纸本)9780769548739
Falls on the stairs are a common cause of accidental injury among the older adults. Understanding the mechanisms leading to such accidents may improve not only the prevention of falls, but also support independent living among elderly. Thus, a method to automatically detect falls and other abnormal events on stairs is presented and empirically validated. Automatic fall detection will also assist in data collection for environmental design improvements and fall prevention. Real-time 3d joint tracking information, provided by a Microsoft Kinect, is used to estimate the walking speed and to extract a set of features that encode humanmotionduring stairway descent. Supervised learning algorithms, trained on manually labelled training data simulated in a home laboratory, obtained a high detection accuracy rate of similar to 92% in leave-one-subject-out cross validation. In contrast with previous research, which identified visual tracking of the feet as the best indicator of dangerous activity, 3dmotion of the hips is experimentally shown to be the most informative component in detecting abnormal events in the 3d tracking data provided by the Kinect.
Recognizing and tracking multiple activities are all extremely challenging machine vision tasks due to diverse motion types included and high-dimensional (Hd) state space. To overcome these difficulties, a novel gener...
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Recognizing and tracking multiple activities are all extremely challenging machine vision tasks due to diverse motion types included and high-dimensional (Hd) state space. To overcome these difficulties, a novel generative model called composite motion model (CMM) is proposed. This model contains a set of independent, low-dimensional (Ld), and activity-specific manifold models that effectively constrain the state search space for 3dhumanmotion recognition and tracking. This separate modeling of activity-specific movements can not only allow each manifold model to be optimized in accordance with only its respective movement, but also improve the scalability of the models. For accurate tracking with our CMM, a particle filter (PF) method is thus employed and then the particles can be distributed in all manifold models at each time step. In addition, an efficient activity switching strategy is proposed to dominate the particle distribution on all Ld manifolds. To diffuse the particles amongst manifold models and respond quickly to the sudden changes in the activity, a set of visually-reasonable and kinematically-realistic transition bridges are synthesized by using the good properties of Ld latent space and Hd observation space, which enables the inter-activity motions seem more natural and realistic. Finally, a pose hypothesis that can best interpret the visual observation is selected and then used to recognize the activity that is currently observed. Extensive experiments, via qualitative and quantitative analyses, verify the effectiveness and robustness of our proposed CMM in the tasks of multi-activity 3dhumanmotion recognition and tracking.
Providing an easy ingress egress (I/E) movement remains a challenge for car designers. I/E has been largely studied in kinematics, but not in dynamics. This study proposes: (1) to evaluate anddescribe the motor torqu...
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Providing an easy ingress egress (I/E) movement remains a challenge for car designers. I/E has been largely studied in kinematics, but not in dynamics. This study proposes: (1) to evaluate anddescribe the motor torques developed in the lower limbs and lumbar joints during I/E motions and (2) to analyse the influence of the car geometry and subject anthropometry. An experiment was performed to observe 15 subjects of three anthropometrical groups getting in and out of a car mock-up simulating three different vehicle configurations. Motor torques were extracted using an inverse dynamics analysis. Both ingress and egress motions were primarily characterised by large torques. Overall, the taller a subject and the lower the seat of the vehicle were, the larger the peak torques were. Moreover, peak torques were higher for egress than ingress. These results are discussed in regard to the current knowledge on I/E ergonomics. Practitioner Summary: Car ingress-egress (I/E) is an ergonomics challenge. Little is known about the physical efforts developed in this motion. developed motor torques were experimentally assessed for three anthropometrical groups and vehicle configurations. Results obtained were discussed in regard to the current knowledge on I/E ergonomics.
3d human motion analysis system is gaining more and more popularity and importance in sports training, game simulation and many other areas. Particle filter algorithm, as a powerful optimized method, can be applied to...
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ISBN:
(纸本)9780769534947
3d human motion analysis system is gaining more and more popularity and importance in sports training, game simulation and many other areas. Particle filter algorithm, as a powerful optimized method, can be applied to 3d human motion analysis system with more accurate results delivered and assured. An improved (hybrid) particle filter algorithm (IPFA) is proposed in this paper which integrates the advantages of partitioned particle filter algorithm (PPFA) with annealed particle filter algorithm (APFA). The results show that, the hybrid algorithm (IPFA) gives rise to more accurate results with less computational time consumed, compared to PPFA and APFA, and improves tracking efficiency and accuracy of 3dhumanmotion substantially.
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