H
Hemerson Tacon
Researcher at Universidade Federal de Juiz de Fora
Publications - 7
Citations - 37
Hemerson Tacon is an academic researcher from Universidade Federal de Juiz de Fora. The author has contributed to research in topics: Convolutional neural network & Deep learning. The author has an hindex of 3, co-authored 7 publications receiving 24 citations.
Papers
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Proceedings ArticleDOI
Multi-stream Convolutional Neural Networks for Action Recognition in Video Sequences Based on Adaptive Visual Rhythms
Darwin Ttito Concha,Helena de Almeida Maia,Helio Pedrini,Hemerson Tacon,André de Souza Brito,Hugo de Lima Chaves,Marcelo Bernardes Vieira +6 more
TL;DR: A multi-stream network is the architecture of choice to incorporate temporal information, since it may benefit from pre-trained deep networks for images and from handcrafted features for initialization, and its training cost is usually lower than video-based networks.
Book ChapterDOI
Human action recognition using convolutional neural networks with symmetric time extension of visual rhythms
Hemerson Tacon,André de Souza Brito,Hugo de Lima Chaves,Marcelo Bernardes Vieira,Saulo Moraes Villela,Helena de Almeida Maia,Darwin Ttito Concha,Helio Pedrini +7 more
TL;DR: This work proposes the usage of multiple Visual Rhythm crops, symmetrically extended in time and separated by a fixed stride, which provide a 2D representation of the video volume matching the fixed input size of the 2D Convolutional Neural Network employed.
Journal ArticleDOI
Weighted voting of multi-stream convolutional neural networks for video-based action recognition using optical flow rhythms
André de Souza Brito,Marcelo Bernardes Vieira,Saulo Moraes Villela,Hemerson Tacon,Hugo de Lima Chaves,Helena de Almeida Maia,Darwin Ttito Concha,Helio Pedrini +7 more
TL;DR: A multi-stream architecture based on the weighted voting of convolutional neural networks to deal with the problem of recognizing human actions in videos is proposed, with a new stream, Optical Flow Rhythm, besides using other streams for diversity.
Book ChapterDOI
Action Recognition in Videos Using Multi-stream Convolutional Neural Networks
Helena de Almeida Maia,Darwin Ttito Concha,Helio Pedrini,Hemerson Tacon,André de Souza Brito,Hugo de Lima Chaves,Marcelo Bernardes Vieira,Saulo Moraes Villela +7 more
TL;DR: A different pre-training procedure for the latter stream is developed using visual rhythm images extracted from a large and challenging video dataset, the Kinetics, which aims to classify trimmed videos based on the action being performed by one or more agents.
Proceedings ArticleDOI
Learnable Visual Rhythms Based on the Stacking of Convolutional Neural Networks for Action Recognition
Helena de Almeida Maia,Marcos Roberto e Souza,Anderson Carlos Sousa e Santos,Helio Pedrini,Hemerson Tacon,André de Souza Brito,Hugo de Lima Chaves,Marcelo Bernardes Vieira,Saulo Moraes Villela +8 more
TL;DR: This work addresses the problem of human action recognition in videos through a multi-stream network that incorporates both spatial and temporal information, and employs a deep network to extract features from the video frames in order to generate the rhythm.