Titlebook: Computer Vision -- ACCV 2014; 12th Asian Conferenc Daniel Cremers,Ian Reid,Ming-Hsuan Yang Conference proceedings 2015 Springer Internation

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Action Recognition in the Presence of One Egocentric and Multiple Static Camerasns are better presented in static cameras, where the whole body of an actor and the context of actions are visible. Some other actions are better recognized in egocentric cameras, where subtle movements of hands and complex object interactions are visible. In this paper, we introduce a model that ca

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HEW

Bi-Stage Large Point Set Registration Using Gaussian Mixture Modelsrrent methods, become extremely slow as the cardinality of the point set increases; making them impractical for large point sets. In this paper, we propose a bi-stage method called bi-GMM-TPS, based on Gaussian Mixture Models and Thin-Plate Splines (GMM-TPS). The first stage deals with global deform

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Enhanced Sequence Matching for Action Recognition from 3D Skeletal Dataect. However, noisy joint position and speed variation between actors make action recognition from 3D joint positions difficult. To address these problems, this paper proposes a novel framework, called Enhanced Sequence Matching (ESM), to align and compare action sequences. Inspired by DNA sequence

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Multi-label Discriminative Weakly-Supervised Human Activity Recognition and Localizationuter interaction to automatic sports commentary. To date, most approaches to video rely on fully supervised settings that require time consuming and error prone manual labeling. Moreover, existing supervised approaches are typically tailored for classification, not detection problems (the spatial an

Stable-Angina

Action-Gons: Action Recognition with a Discriminative Dictionary of Structured Elements with Varyingularity seen in human behavior, as well as a large degree of variation. One key property of action, compared with image scene, might be the amount of interaction among body parts, although scenes also observe structured patterns in 2D images. Here, we study high-order statistics of the interaction a

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