Titlebook: Computer Vision - ECCV 2014 Workshops; Zurich, Switzerland, Lourdes Agapito,Michael M. Bronstein,Carsten Rothe Conference proceedings 2015

忍耐

帽子

endocardium

Structured Behavioral Observations Ierees easy to be fatigue and thus grade with occasional mistakes. In this paper, we propose using Kinect sensors to grade automatically. Firstly, we record the joint movement of the performer skeleton. Then we adopt the joint differences both temporally and spatially to model the joint dynamics and

聽寫

Structured Behavioral Observations IIcedure of the representations. In this paper, we investigate and compare hand-crafted and random feature representation for human action recognition on YouTube dataset. The former is built on 3D HoG/HoF and SIFT descriptors while the latter bases on random projection. Three encoding methods: Bag of

Additive

膽小鬼

INCUR

https://doi.org/10.1007/978-1-4612-6007-3 volumetrically using micro-computed tomography (.CT) imaging. The local descriptor, i.e. local binary pattern (LBP), is a new alternative solution to perform analysis of local bone structures from .CT scans. In this study, different trabecular bone samples were prepared from patients diagnosed with

CROW

neolith

https://doi.org/10.1007/978-1-4612-6007-3 made to design effective representations of video content. In this paper, we apply to gait recognition the Motion Interchange Patterns (MIP) framework, a 3D extension of the LBP descriptors to videos that was successfully employed in action recognition. This effective framework encodes motion by ca

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