Ego-Lane Analysis System - Histórico de revisão

Rodrigo Berriel: bug double-curly-braces

2018-03-01T12:10:10Z

bug double-curly-braces

Rodrigo Berriel: correção link e bibtex

2018-03-01T12:06:58Z

correção link e bibtex

Rodrigo Berriel: add links

2017-09-25T17:35:24Z

add links

Rodrigo Berriel: doi and bibtex

2017-08-13T13:31:57Z

doi and bibtex

Rodrigo Berriel: add na categoria

2017-03-25T16:45:47Z

add na categoria

Rodrigo Berriel: adição de imagens

2017-02-03T17:46:03Z

adição de imagens

Rodrigo Berriel: /* Dataset */

2016-09-05T14:17:47Z

‎Dataset

Rodrigo Berriel em 14h10min de 5 de setembro de 2016

2016-09-05T14:10:05Z

Rodrigo Berriel em 12h32min de 9 de agosto de 2016

2016-08-09T12:32:14Z

Rodrigo Berriel: adicionei ponteiro para o outro vídeo e outro para uma imagem da IARA

2016-08-09T12:30:59Z

adicionei ponteiro para o outro vídeo e outro para uma imagem da IARA

@@ Linha 38: / Linha 38: @@
    @article{berriel2017imavis,
      Author  = {Rodrigo F. Berriel and Edilson de Aguiar and Alberto F. de Souza and Thiago Oliveira-Santos},
-     Title   = {{Ego-Lane Analysis System (ELAS): Dataset and Algorithms}},
+     Title   = &#123;&#123;Ego-Lane Analysis System (ELAS): Dataset and Algorithms}},
      Journal = {Image and Vision Computing},
      Volume  = {68},

@@ Linha 28: / Linha 28: @@
 It contains 22 scenes with a total of 17,092 frames. In 98.54% of the frames, at least one of the sides has white lane markings, while 12.88% of them are yellow. In 5.18% of the frames at least one side has no lane markings. This numbers include frames containing transitions of lane markings type, i.e. images with two lane markings type simultaneously on the same side. Lane markings type transitions are present in 1,854 frames (10.85%). Lane change maneuver are being performed in 5.42% of this dataset, where 64.72% is from right to left and 35.28% in the opposite direction. There are intersections in 2.11% of the frames. In 7.28% of all images, there is at least one pavement marking. 33.92% of the pavement markings are crosswalks and 15.27% are annotated as unknown, i.e. they are of none of the classes of interest and 50.81% comprises arrows and stop lines. There is at least one adjacent lane in 50.34% and 72.14% of the frames for each side, right and left respectively.
-[http://www.lcad.inf.ufes.br/~berriel/paper-si-auto-vision/dataset-short-description.pdf Download a short description of each scene (with images).]
+[https://drive.google.com/open?id=1sIgybW-V3mrJ_CkjiC_IS2zEZjDJ5Pm2 Download a short description of each scene (with images).]
 Some samples below:
@@ Linha 36: / Linha 36: @@
 == BibTeX ==
-   @article{Berriel2017imavis,
+   @article{berriel2017imavis,
-     author  = "Rodrigo F. Berriel and Edilson de Aguiar and Alberto F. de Souza and Thiago Oliveira-Santos",
+     Author  = {Rodrigo F. Berriel and Edilson de Aguiar and Alberto F. de Souza and Thiago Oliveira-Santos},
-     title   = "Ego-Lane Analysis System (ELAS): Dataset and Algorithms",
+     Title   = {{Ego-Lane Analysis System (ELAS): Dataset and Algorithms}},
-     journal = "Image and Vision Computing",
+     Journal = {Image and Vision Computing},
-     year    = "2017",
+     Volume  = {68},
-     note    = "In Press",
+     Pages   = {64--75}
-     issn    = "0262-8856",
+     Year    = {2017},
-     doi     = "https://doi.org/10.1016/j.imavis.2017.07.005",
+     DOI     = {10.1016/J.IMAVIS.2017.07.005},
+   }

@@ Linha 21: / Linha 21: @@
 == Source-Code ==
-Available upon acceptance.
+Available [https://github.com/rodrigoberriel/ego-lane-analysis-system here]
 == Dataset ==
-Available upon acceptance.
+To request access to the datasets, read the instructions [https://github.com/rodrigoberriel/ego-lane-analysis-system/blob/master/datasets/ here].
 It contains 22 scenes with a total of 17,092 frames. In 98.54% of the frames, at least one of the sides has white lane markings, while 12.88% of them are yellow. In 5.18% of the frames at least one side has no lane markings. This numbers include frames containing transitions of lane markings type, i.e. images with two lane markings type simultaneously on the same side. Lane markings type transitions are present in 1,854 frames (10.85%). Lane change maneuver are being performed in 5.42% of this dataset, where 64.72% is from right to left and 35.28% in the opposite direction. There are intersections in 2.11% of the frames. In 7.28% of all images, there is at least one pavement marking. 33.92% of the pavement markings are crosswalks and 15.27% are annotated as unknown, i.e. they are of none of the classes of interest and 50.81% comprises arrows and stop lines. There is at least one adjacent lane in 50.34% and 72.14% of the frames for each side, right and left respectively.

@@ Linha 2: / Linha 2: @@
 Authors: [http://rodrigoberriel.com/ Rodrigo Berriel], [http://people.mpi-inf.mpg.de/~edeaguia/ Edilson de Aguiar], [http://www.lcad.inf.ufes.br/team/index.php/Prof._Dr._Alberto_Ferreira_De_Souza Alberto F. de Souza], [http://www.inf.ufes.br/~todsantos/home Thiago Oliveira-Santos]
-''This paper is under review (Special Issue: Automotive Vision, Image and Vision Computing)''
+'''Image and Vision Computing''': [https://doi.org/10.1016/j.imavis.2017.07.005 10.1016/j.imavis.2017.07.005]
 == Abstract ==
@@ Linha 33: / Linha 33: @@
 [[Arquivo:Elas-dataset-samples.png|x300px]]

← Edição anterior		Edição das 16h45min de 25 de março de 2017
Linha 1:		Linha 1:
		+	[[category:Publicações]]
	Authors: [http://rodrigoberriel.com/ Rodrigo Berriel], [http://people.mpi-inf.mpg.de/~edeaguia/ Edilson de Aguiar], [http://www.lcad.inf.ufes.br/team/index.php/Prof._Dr._Alberto_Ferreira_De_Souza Alberto F. de Souza], [http://www.inf.ufes.br/~todsantos/home Thiago Oliveira-Santos]		Authors: [http://rodrigoberriel.com/ Rodrigo Berriel], [http://people.mpi-inf.mpg.de/~edeaguia/ Edilson de Aguiar], [http://www.lcad.inf.ufes.br/team/index.php/Prof._Dr._Alberto_Ferreira_De_Souza Alberto F. de Souza], [http://www.inf.ufes.br/~todsantos/home Thiago Oliveira-Santos]

@@ Linha 15: / Linha 15: @@
 Available upon acceptance.
-It contains 22 scenes with a total of 17,092 frames. In 98.54% of the frames, at least one of the sides has white lane markings, while 12.88% of them are yellow. In 5.18% of the frames at least one side has no lane markings. This numbers include frames containing transitions of lane markings type, i.e. images with two lane markings type simultaneously. Lane markings type transitions are present in 1,854 frames (10.85%). Lane change maneuver are being performed in 5.42% of this dataset, where 64.72% is from right to left and 35.28% in the opposite direction. There are intersections in 2.11% of the frames. In 7.28% of all images, there is at least one pavement marking. 33.92% of the pavement markings are crosswalks and 15.27% are annotated as unknown, i.e. they are of none of the classes of interest and 50.81% comprises arrows and stop lines. There is at least one adjacent lane in 50.34% and 72.14% of the frames for each side, right and left respectively.
+It contains 22 scenes with a total of 17,092 frames. In 98.54% of the frames, at least one of the sides has white lane markings, while 12.88% of them are yellow. In 5.18% of the frames at least one side has no lane markings. This numbers include frames containing transitions of lane markings type, i.e. images with two lane markings type simultaneously on the same side. Lane markings type transitions are present in 1,854 frames (10.85%). Lane change maneuver are being performed in 5.42% of this dataset, where 64.72% is from right to left and 35.28% in the opposite direction. There are intersections in 2.11% of the frames. In 7.28% of all images, there is at least one pavement marking. 33.92% of the pavement markings are crosswalks and 15.27% are annotated as unknown, i.e. they are of none of the classes of interest and 50.81% comprises arrows and stop lines. There is at least one adjacent lane in 50.34% and 72.14% of the frames for each side, right and left respectively.
 [http://www.lcad.inf.ufes.br/~berriel/paper-si-auto-vision/dataset-short-description.pdf Short description of each scene.]

@@ Linha 11: / Linha 11: @@
 == Demonstration Video ==
 [http://bit.ly/SI-AUTO-VISION_DEMO-VIDEO Demonstration Video of ELAS]
 == Dataset ==