Titlebook: Machine Learning for Vision-Based Motion Analysis; Theory and Technique Liang Wang,Guoying Zhao,Matti Pietikäinen Book 2011 Springer-Verlag

BULB

书目名称Machine Learning for Vision-Based Motion Analysis影响因子(影响力)




书目名称Machine Learning for Vision-Based Motion Analysis影响因子(影响力)学科排名




书目名称Machine Learning for Vision-Based Motion Analysis网络公开度




书目名称Machine Learning for Vision-Based Motion Analysis网络公开度学科排名




书目名称Machine Learning for Vision-Based Motion Analysis被引频次




书目名称Machine Learning for Vision-Based Motion Analysis被引频次学科排名




书目名称Machine Learning for Vision-Based Motion Analysis年度引用




书目名称Machine Learning for Vision-Based Motion Analysis年度引用学科排名




书目名称Machine Learning for Vision-Based Motion Analysis读者反馈




书目名称Machine Learning for Vision-Based Motion Analysis读者反馈学科排名

欲望

Manifold Learning for Multi-dimensional Auto-regressive Dynamical Models multidimensional autoregressive models of order 2. Experimental results concerning identity recognition are shown that prove how such optimal pullback Fisher metrics greatly improve classification performances.

联邦

Discriminative Multiple Target Trackingimplicit exclusive principle is naturally reinforced in the proposed framework, which renders the tracker to be robust to cross occlusions among the multiple targets. We demonstrate the efficacy of the proposed multiple target tracker on benchmark visual tracking sequences, and real-world video sequences as well.

大方不好

Recognition of Spatiotemporal Gestures in Sign Language Using Gesture Threshold HMMs system included testing the performance of conditional random fields (CRF), hidden CRF (HCRF) and latent-dynamic CRF (LDCRF) based systems and comparing these to our GT-HMM based system when recognizing motion gestures and identifying inter gesture transitions.

高原

Customary

改变

Learning Behavioral Patterns of Time Series for Video-Surveillanceupervised and unsupervised settings and is based on a set of loosely labeled data acquired by a real video-surveillance system. The experiments highlight different peculiarities of the methods taken into consideration, and the final discussion guides the reader towards the most appropriate choice for a given scenario.

AWL

2191-6586 ffective vision-based motion understanding from a machine le.Techniques of vision-based motion analysis aim to detect, track, identify, and generally understand the behavior of objects in image sequences. With the growth of video data in a wide range of applications from visual surveillance to human

妨碍

头盔

Mixed-State Markov Models in Image Motion Analysisn of mixed-state models to motion texture analysis. Motion textures correspond to the instantaneous apparent motion maps extracted from dynamic textures. They depict mixed-state motion values with a discrete state at zero and a Gaussian distribution for the rest. Mixed-state Markov random fields and