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Action tube extraction based 3D-CNN for RGB-D action recognition

Xu, Z.; Vilaplana, V.; Morros, J.R.
Tipus d'activitat
Presentació treball a congrés
Nom de l'edició
16th International Conference on Content-Based Multimedia Indexing
Any de l'edició
Data de presentació
Llibre d'actes
16th International Conference on Content-Based Multimedia Indexing: 4-6 September, 2018 La Rochelle, France
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Repositori Obrir en finestra nova
In this paper we propose a novel action tube extractor for RGB-D action recognition in trimmed videos. The action tube extractor takes as input a video and outputs an action tube. The method consists of two parts: spatial tube extraction and temporal sampling. The first part is built upon MobileNet-SSD and its role is to define the spatial region where the action takes place. The second part is based on the structural similarity index (SSIM) and is designed to remove frames without obvious motio...
Paraules clau
3D-CNN, CNN models, action recognition, action tube extraction extraction, indexing (of information), spatial regions, state-of-the-art methods, structural similarity indices (SSIM), temporal sampling, tubes (components), two-stream
Grup de recerca
GPI - Grup de Processament d'Imatge i Vídeo
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center