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Image Analysis and Machine Learning

R-COVNET: RECURRENT NEURAL CONVOLUTION NETWORK FOR 3D OBJECT RECOGNITION


Point cloud are precise digital record of an objects in space. It starts to getting more attention due to the additional information it provides compared to 2D images. In this paper, we propose a new deep learning architecture called R-CovNets, designed for 3D object recognition. Unlike to previous approaches that usually sample or convert point cloud into three-dimensional grids, R-CovNets does not reckon on any preprocessing. Our architecture is specially designed for cloud point, permutation invariant and can take as input, a data of any size.

R-COVNET.pdf

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Authors:
Danielle Tchuinkou Kwadj and Christophe Bobda
Submitted On:
8 October 2018 - 2:07pm
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R-COVNET.pdf

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[1] Danielle Tchuinkou Kwadj and Christophe Bobda, "R-COVNET: RECURRENT NEURAL CONVOLUTION NETWORK FOR 3D OBJECT RECOGNITION", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3638. Accessed: Nov. 19, 2018.
@article{3638-18,
url = {http://sigport.org/3638},
author = {Danielle Tchuinkou Kwadj and Christophe Bobda },
publisher = {IEEE SigPort},
title = {R-COVNET: RECURRENT NEURAL CONVOLUTION NETWORK FOR 3D OBJECT RECOGNITION},
year = {2018} }
TY - EJOUR
T1 - R-COVNET: RECURRENT NEURAL CONVOLUTION NETWORK FOR 3D OBJECT RECOGNITION
AU - Danielle Tchuinkou Kwadj and Christophe Bobda
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3638
ER -
Danielle Tchuinkou Kwadj and Christophe Bobda. (2018). R-COVNET: RECURRENT NEURAL CONVOLUTION NETWORK FOR 3D OBJECT RECOGNITION. IEEE SigPort. http://sigport.org/3638
Danielle Tchuinkou Kwadj and Christophe Bobda, 2018. R-COVNET: RECURRENT NEURAL CONVOLUTION NETWORK FOR 3D OBJECT RECOGNITION. Available at: http://sigport.org/3638.
Danielle Tchuinkou Kwadj and Christophe Bobda. (2018). "R-COVNET: RECURRENT NEURAL CONVOLUTION NETWORK FOR 3D OBJECT RECOGNITION." Web.
1. Danielle Tchuinkou Kwadj and Christophe Bobda. R-COVNET: RECURRENT NEURAL CONVOLUTION NETWORK FOR 3D OBJECT RECOGNITION [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3638

AUTOMATIC TEMPORAL SEGMENTATION OF HAND MOVEMENTS FOR HAND POSITIONS RECOGNITION IN FRENCH CUED SPEECH


In the context of Cued Speech (CS) recognition, the recognition
of lips and hand movements is a key task. As we know, a good
temporal segmentation is necessary for the supervised recog-
nition system. However, lips and hand streams cannot share
the same temporal segmentation since they are not synchro-
nized. In this work, we propose a hand preceding model to
predict temporal segmentations of hand movements automati-
cally by exploring the relationship between hand preceding time

Paper Details

Authors:
LI LIU, GANG FENG, DENIS BEAUTEMPS
Submitted On:
20 April 2018 - 1:08am
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Poster_ICASSP_36032018.pdf

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[1] LI LIU, GANG FENG, DENIS BEAUTEMPS, "AUTOMATIC TEMPORAL SEGMENTATION OF HAND MOVEMENTS FOR HAND POSITIONS RECOGNITION IN FRENCH CUED SPEECH", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3072. Accessed: Nov. 19, 2018.
@article{3072-18,
url = {http://sigport.org/3072},
author = {LI LIU; GANG FENG; DENIS BEAUTEMPS },
publisher = {IEEE SigPort},
title = {AUTOMATIC TEMPORAL SEGMENTATION OF HAND MOVEMENTS FOR HAND POSITIONS RECOGNITION IN FRENCH CUED SPEECH},
year = {2018} }
TY - EJOUR
T1 - AUTOMATIC TEMPORAL SEGMENTATION OF HAND MOVEMENTS FOR HAND POSITIONS RECOGNITION IN FRENCH CUED SPEECH
AU - LI LIU; GANG FENG; DENIS BEAUTEMPS
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3072
ER -
LI LIU, GANG FENG, DENIS BEAUTEMPS. (2018). AUTOMATIC TEMPORAL SEGMENTATION OF HAND MOVEMENTS FOR HAND POSITIONS RECOGNITION IN FRENCH CUED SPEECH. IEEE SigPort. http://sigport.org/3072
LI LIU, GANG FENG, DENIS BEAUTEMPS, 2018. AUTOMATIC TEMPORAL SEGMENTATION OF HAND MOVEMENTS FOR HAND POSITIONS RECOGNITION IN FRENCH CUED SPEECH. Available at: http://sigport.org/3072.
LI LIU, GANG FENG, DENIS BEAUTEMPS. (2018). "AUTOMATIC TEMPORAL SEGMENTATION OF HAND MOVEMENTS FOR HAND POSITIONS RECOGNITION IN FRENCH CUED SPEECH." Web.
1. LI LIU, GANG FENG, DENIS BEAUTEMPS. AUTOMATIC TEMPORAL SEGMENTATION OF HAND MOVEMENTS FOR HAND POSITIONS RECOGNITION IN FRENCH CUED SPEECH [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3072