|
Records |
Links |
|
Author |
Ferran Diego; Daniel Ponsa; Joan Serrat; Antonio Lopez |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
Video Alignment for Difference-spotting |
Type |
Miscellaneous |
|
Year |
2008 |
Publication |
Proceedings of the ECCV workshop on Multi–camera and Multi–modal Sensor Fusion Algorithms and Applications (M2SFA2 2008), Marseille (France) |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
video alignment |
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
ADAS @ adas @ DPS2008 |
Serial |
1079 |
|
Permanent link to this record |
|
|
|
|
Author |
Ferran Diego; Daniel Ponsa; Joan Serrat; Antonio Lopez |
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Video alignment for automotive applications |
Type |
Miscellaneous |
|
Year |
2009 |
Publication |
BMVA one–day technical meeting on vision for automotive applications |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
video alignment |
|
|
Abstract |
|
|
|
Address |
London, UK |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
ADAS @ adas @ DPS2009 |
Serial |
1271 |
|
Permanent link to this record |
|
|
|
|
Author |
Ferran Diego; Daniel Ponsa; Joan Serrat; Antonio Lopez |
![download PDF file pdf](img/file_PDF.gif)
![find book details (via ISBN) isbn](img/isbn.gif)
|
|
Title |
Vehicle geolocalization based on video synchronization |
Type |
Conference Article |
|
Year |
2010 |
Publication |
13th Annual International Conference on Intelligent Transportation Systems |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
1511–1516 |
|
|
Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
video alignment |
|
|
Abstract |
TC8.6
This paper proposes a novel method for estimating the geospatial localization of a vehicle. I uses as input a georeferenced video sequence recorded by a forward-facing camera attached to the windscreen. The core of the proposed method is an on-line video synchronization which finds out the corresponding frame in the georeferenced video sequence to the one recorded at each time by the camera on a second drive through the same track. Once found the corresponding frame in the georeferenced video sequence, we transfer its geospatial information of this frame. The key advantages of this method are: 1) the increase of the update rate and the geospatial accuracy with regard to a standard low-cost GPS and 2) the ability to localize a vehicle even when a GPS is not available or is not reliable enough, like in certain urban areas. Experimental results for an urban environments are presented, showing an average of relative accuracy of 1.5 meters. |
|
|
Address |
Madeira Island (Portugal) |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
2153-0009 |
ISBN |
978-1-4244-7657-2 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ITSC |
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
ADAS @ adas @ DPS2010 |
Serial |
1423 |
|
Permanent link to this record |
|
|
|
|
Author |
Ferran Diego; Daniel Ponsa; Joan Serrat; Antonio Lopez |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
Video Alignment for Change Detection |
Type |
Journal Article |
|
Year |
2011 |
Publication |
IEEE Transactions on Image Processing |
Abbreviated Journal |
TIP |
|
|
Volume |
20 |
Issue |
7 |
Pages |
1858-1869 |
|
|
Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
video alignment |
|
|
Abstract |
In this work, we address the problem of aligning two video sequences. Such alignment refers to synchronization, i.e., the establishment of temporal correspondence between frames of the first and second video, followed by spatial registration of all the temporally corresponding frames. Video synchronization and alignment have been attempted before, but most often in the relatively simple cases of fixed or rigidly attached cameras and simultaneous acquisition. In addition, restrictive assumptions have been applied, including linear time correspondence or the knowledge of the complete trajectories of corresponding scene points; to some extent, these assumptions limit the practical applicability of any solutions developed. We intend to solve the more general problem of aligning video sequences recorded by independently moving cameras that follow similar trajectories, based only on the fusion of image intensity and GPS information. The novelty of our approach is to pose the synchronization as a MAP inference problem on a Bayesian network including the observations from these two sensor types, which have been proved complementary. Alignment results are presented in the context of videos recorded from vehicles driving along the same track at different times, for different road types. In addition, we explore two applications of the proposed video alignment method, both based on change detection between aligned videos. One is the detection of vehicles, which could be of use in ADAS. The other is online difference spotting videos of surveillance rounds. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS; IF |
Approved |
no |
|
|
Call Number |
DPS 2011; ADAS @ adas @ dps2011 |
Serial |
1705 |
|
Permanent link to this record |
|
|
|
|
Author |
G.D. Evangelidis; Ferran Diego; Joan Serrat; Antonio Lopez |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
Slice Matching for Accurate Spatio-Temporal Alignment |
Type |
Conference Article |
|
Year |
2011 |
Publication |
In ICCV Workshop on Visual Surveillance |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
video alignment |
|
|
Abstract |
Video synchronization and alignment is a rather recent topic in computer vision. It usually deals with the problem of aligning sequences recorded simultaneously by static, jointly- or independently-moving cameras. In this paper, we investigate the more difficult problem of matching videos captured at different times from independently-moving cameras, whose trajectories are approximately coincident or parallel. To this end, we propose a novel method that pixel-wise aligns videos and allows thus to automatically highlight their differences. This primarily aims at visual surveillance but the method can be adopted as is by other related video applications, like object transfer (augmented reality) or high dynamic range video. We build upon a slice matching scheme to first synchronize the sequences, while we develop a spatio-temporal alignment scheme to spatially register corresponding frames and refine the temporal mapping. We investigate the performance of the proposed method on videos recorded from vehicles driven along different types of roads and compare with related previous works. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
VS |
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
Admin @ si @ EDS2011; ADAS @ adas @ eds2011a |
Serial |
1861 |
|
Permanent link to this record |
|
|
|
|
Author |
Ferran Diego; Joan Serrat; Antonio Lopez |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Joint spatio-temporal alignment of sequences |
Type |
Journal Article |
|
Year |
2013 |
Publication |
IEEE Transactions on Multimedia |
Abbreviated Journal |
TMM |
|
|
Volume |
15 |
Issue |
6 |
Pages |
1377-1387 |
|
|
Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
video alignment |
|
|
Abstract |
Video alignment is important in different areas of computer vision such as wide baseline matching, action recognition, change detection, video copy detection and frame dropping prevention. Current video alignment methods usually deal with a relatively simple case of fixed or rigidly attached cameras or simultaneous acquisition. Therefore, in this paper we propose a joint video alignment for bringing two video sequences into a spatio-temporal alignment. Specifically, the novelty of the paper is to formulate the video alignment to fold the spatial and temporal alignment into a single alignment framework. This simultaneously satisfies a frame-correspondence and frame-alignment similarity; exploiting the knowledge among neighbor frames by a standard pairwise Markov random field (MRF). This new formulation is able to handle the alignment of sequences recorded at different times by independent moving cameras that follows a similar trajectory, and also generalizes the particular cases that of fixed geometric transformation and/or linear temporal mapping. We conduct experiments on different scenarios such as sequences recorded simultaneously or by moving cameras to validate the robustness of the proposed approach. The proposed method provides the highest video alignment accuracy compared to the state-of-the-art methods on sequences recorded from vehicles driving along the same track at different times. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
1520-9210 |
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
Admin @ si @ DSL2013; ADAS @ adas @ |
Serial |
2228 |
|
Permanent link to this record |
|
|
|
|
Author |
Ferran Diego; Jose Manuel Alvarez; Joan Serrat; Antonio Lopez |
![download PDF file pdf](img/file_PDF.gif)
![find book details (via ISBN) isbn](img/isbn.gif)
|
|
Title |
Vision-based road detection via on-line video registration |
Type |
Conference Article |
|
Year |
2010 |
Publication |
13th Annual International Conference on Intelligent Transportation Systems |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
1135–1140 |
|
|
Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
video alignment; road detection |
|
|
Abstract |
TB6.2
Road segmentation is an essential functionality for supporting advanced driver assistance systems (ADAS) such as road following and vehicle and pedestrian detection. Significant efforts have been made in order to solve this task using vision-based techniques. The major challenge is to deal with lighting variations and the presence of objects on the road surface. In this paper, we propose a new road detection method to infer the areas of the image depicting road surfaces without performing any image segmentation. The idea is to previously segment manually or semi-automatically the road region in a traffic-free reference video record on a first drive. And then to transfer these regions to the frames of a second video sequence acquired later in a second drive through the same road, in an on-line manner. This is possible because we are able to automatically align the two videos in time and space, that is, to synchronize them and warp each frame of the first video to its corresponding frame in the second one. The geometric transform can thus transfer the road region to the present frame on-line. In order to reduce the different lighting conditions which are present in outdoor scenarios, our approach incorporates a shadowless feature space which represents an image in an illuminant-invariant feature space. Furthermore, we propose a dynamic background subtraction algorithm which removes the regions containing vehicles in the observed frames which are within the transferred road region. |
|
|
Address |
Madeira Island (Portugal) |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
2153-0009 |
ISBN |
978-1-4244-7657-2 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ITSC |
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
ADAS @ adas @ DAS2010 |
Serial |
1424 |
|
Permanent link to this record |
|
|
|
|
Author |
Henry Velesaca; Patricia Suarez; Angel Sappa; Dario Carpio; Rafael E. Rivadeneira; Angel Sanchez |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Review on Common Techniques for Urban Environment Video Analytics |
Type |
Conference Article |
|
Year |
2022 |
Publication |
Anais do III Workshop Brasileiro de Cidades Inteligentes |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
107-118 |
|
|
Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
Video Analytics; Review; Urban Environments; Smart Cities |
|
|
Abstract |
This work compiles the different computer vision-based approaches
from the state-of-the-art intended for video analytics in urban environments.
The manuscript groups the different approaches according to the typical modules present in video analysis, including image preprocessing, object detection,
classification, and tracking. This proposed pipeline serves as a basic guide to
representing these most representative approaches in this topic of video analysis
that will be addressed in this work. Furthermore, the manuscript is not intended
to be an exhaustive review of the most advanced approaches, but only a list of
common techniques proposed to address recurring problems in this field. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
WBCI |
|
|
Notes |
MSIAU; 601.349 |
Approved |
no |
|
|
Call Number |
Admin @ si @ VSS2022 |
Serial |
3773 |
|
Permanent link to this record |
|
|
|
|
Author |
Chengyi Zou; Shuai Wan; Marta Mrak; Marc Gorriz Blanch; Luis Herranz; Tiannan Ji |
![goto web page url](img/www.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Towards Lightweight Neural Network-based Chroma Intra Prediction for Video Coding |
Type |
Conference Article |
|
Year |
2022 |
Publication |
29th IEEE International Conference on Image Processing |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
Video coding; Quantization (signal); Computational modeling; Neural networks; Predictive models; Video compression; Syntactics |
|
|
Abstract |
In video compression the luma channel can be useful for predicting chroma channels (Cb, Cr), as has been demonstrated with the Cross-Component Linear Model (CCLM) used in Versatile Video Coding (VVC) standard. More recently, it has been shown that neural networks can even better capture the relationship among different channels. In this paper, a new attention-based neural network is proposed for cross-component intra prediction. With the goal to simplify neural network design, the new framework consists of four branches: boundary branch and luma branch for extracting features from reference samples, attention branch for fusing the first two branches, and prediction branch for computing the predicted chroma samples. The proposed scheme is integrated into VVC test model together with one additional binary block-level syntax flag which indicates whether a given block makes use of the proposed method. Experimental results demonstrate 0.31%/2.36%/2.00% BD-rate reductions on Y/Cb/Cr components, respectively, on top of the VVC Test Model (VTM) 7.0 which uses CCLM. |
|
|
Address |
Bordeaux; France; October 2022 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICIP |
|
|
Notes |
MACO |
Approved |
no |
|
|
Call Number |
Admin @ si @ ZWM2022 |
Serial |
3790 |
|
Permanent link to this record |
|
|
|
|
Author |
Alvaro Peris; Marc Bolaños; Petia Radeva; Francisco Casacuberta |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
Video Description Using Bidirectional Recurrent Neural Networks |
Type |
Conference Article |
|
Year |
2016 |
Publication |
25th International Conference on Artificial Neural Networks |
Abbreviated Journal |
|
|
|
Volume |
2 |
Issue |
|
Pages |
3-11 |
|
|
Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
Video description; Neural Machine Translation; Birectional Recurrent Neural Networks; LSTM; Convolutional Neural Networks |
|
|
Abstract |
Although traditionally used in the machine translation field, the encoder-decoder framework has been recently applied for the generation of video and image descriptions. The combination of Convolutional and Recurrent Neural Networks in these models has proven to outperform the previous state of the art, obtaining more accurate video descriptions. In this work we propose pushing further this model by introducing two contributions into the encoding stage. First, producing richer image representations by combining object and location information from Convolutional Neural Networks and second, introducing Bidirectional Recurrent Neural Networks for capturing both forward and backward temporal relationships in the input frames. |
|
|
Address |
Barcelona; September 2016 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICANN |
|
|
Notes |
MILAB; |
Approved |
no |
|
|
Call Number |
Admin @ si @ PBR2016 |
Serial |
2833 |
|
Permanent link to this record |
|
|
|
|
Author |
Weijia Wu; Yuzhong Zhao; Zhuang Li; Jiahong Li; Mike Zheng Shou; Umapada Pal; Dimosthenis Karatzas; Xiang Bai |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
ICDAR 2023 Competition on Video Text Reading for Dense and Small Text |
Type |
Conference Article |
|
Year |
2023 |
Publication |
17th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
14188 |
Issue |
|
Pages |
405–419 |
|
|
Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
Video Text Spotting; Small Text; Text Tracking; Dense Text |
|
|
Abstract |
Recently, video text detection, tracking and recognition in natural scenes are becoming very popular in the computer vision community. However, most existing algorithms and benchmarks focus on common text cases (e.g., normal size, density) and single scenario, while ignore extreme video texts challenges, i.e., dense and small text in various scenarios. In this competition report, we establish a video text reading benchmark, named DSText, which focuses on dense and small text reading challenge in the video with various scenarios. Compared with the previous datasets, the proposed dataset mainly include three new challenges: 1) Dense video texts, new challenge for video text spotter. 2) High-proportioned small texts. 3) Various new scenarios, e.g., ‘Game’, ‘Sports’, etc. The proposed DSText includes 100 video clips from 12 open scenarios, supporting two tasks (i.e., video text tracking (Task 1) and end-to-end video text spotting (Task2)). During the competition period (opened on 15th February, 2023 and closed on 20th March, 2023), a total of 24 teams participated in the three proposed tasks with around 30 valid submissions, respectively. In this article, we describe detailed statistical information of the dataset, tasks, evaluation protocols and the results summaries of the ICDAR 2023 on DSText competition. Moreover, we hope the benchmark will promise the video text research in the community. |
|
|
Address |
San Jose; CA; USA; August 2023 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICDAR |
|
|
Notes |
DAG |
Approved |
no |
|
|
Call Number |
Admin @ si @ WZL2023 |
Serial |
3898 |
|
Permanent link to this record |
|
|
|
|
Author |
Pejman Rasti; Salma Samiei; Mary Agoyi; Sergio Escalera; Gholamreza Anbarjafari |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Robust non-blind color video watermarking using QR decomposition and entropy analysis |
Type |
Journal Article |
|
Year |
2016 |
Publication |
Journal of Visual Communication and Image Representation |
Abbreviated Journal |
JVCIR |
|
|
Volume |
38 |
Issue |
|
Pages |
838-847 |
|
|
Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
Video watermarking; QR decomposition; Discrete Wavelet Transformation; Chirp Z-transform; Singular value decomposition; Orthogonal–triangular decomposition |
|
|
Abstract |
Issues such as content identification, document and image security, audience measurement, ownership and copyright among others can be settled by the use of digital watermarking. Many recent video watermarking methods show drops in visual quality of the sequences. The present work addresses the aforementioned issue by introducing a robust and imperceptible non-blind color video frame watermarking algorithm. The method divides frames into moving and non-moving parts. The non-moving part of each color channel is processed separately using a block-based watermarking scheme. Blocks with an entropy lower than the average entropy of all blocks are subject to a further process for embedding the watermark image. Finally a watermarked frame is generated by adding moving parts to it. Several signal processing attacks are applied to each watermarked frame in order to perform experiments and are compared with some recent algorithms. Experimental results show that the proposed scheme is imperceptible and robust against common signal processing attacks. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
HuPBA;MILAB; |
Approved |
no |
|
|
Call Number |
Admin @ si @RSA2016 |
Serial |
2766 |
|
Permanent link to this record |
|
|
|
|
Author |
Carles Sanchez; Debora Gil; Antoni Rosell; Albert Andaluz; F. Javier Sanchez |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Segmentation of Tracheal Rings in Videobronchoscopy combining Geometry and Appearance |
Type |
Conference Article |
|
Year |
2013 |
Publication |
Proceedings of the International Conference on Computer Vision Theory and Applications |
Abbreviated Journal |
|
|
|
Volume |
1 |
Issue |
|
Pages |
153--161 |
|
|
Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
Video-bronchoscopy, tracheal ring segmentation, trachea geometric and appearance model |
|
|
Abstract |
Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways and minimal invasive interventions. Tracheal procedures are ordinary interventions that require measurement of the percentage of obstructed pathway for injury (stenosis) assessment. Visual assessment of stenosis in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error. Accurate detection of tracheal rings is the basis for automated estimation of the size of stenosed trachea. Processing of videobronchoscopic images acquired at the operating room is a challenging task due to the wide range of artifacts and acquisition conditions. We present a model of the geometric-appearance of tracheal rings for its detection in videobronchoscopic videos. Experiments on sequences acquired at the operating room, show a performance close to inter-observer variability |
|
|
Address |
Barcelona; February 2013 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
SciTePress |
Place of Publication |
Portugal |
Editor |
Sebastiano Battiato and José Braz |
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-989-8565-47-1 |
Medium |
|
|
|
Area |
800 |
Expedition |
|
Conference |
VISAPP |
|
|
Notes |
IAM;MV; 600.044; 600.047; 600.060; 605.203 |
Approved |
no |
|
|
Call Number |
IAM @ iam @ SGR2013 |
Serial |
2123 |
|
Permanent link to this record |
|
|
|
|
Author |
Carles Sanchez; Antonio Esteban Lansaque; Agnes Borras; Marta Diez-Ferrer; Antoni Rosell; Debora Gil |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
Towards a Videobronchoscopy Localization System from Airway Centre Tracking |
Type |
Conference Article |
|
Year |
2017 |
Publication |
12th International Conference on Computer Vision Theory and Applications |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
352-359 |
|
|
Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
Video-bronchoscopy; Lung cancer diagnosis; Airway lumen detection; Region tracking; Guided bronchoscopy navigation |
|
|
Abstract |
Bronchoscopists use fluoroscopy to guide flexible bronchoscopy to the lesion to be biopsied without any kind of incision. Being fluoroscopy an imaging technique based on X-rays, the risk of developmental problems and cancer is increased in those subjects exposed to its application, so minimizing radiation is crucial. Alternative guiding systems such as electromagnetic navigation require specific equipment, increase the cost of the clinical procedure and still require fluoroscopy. In this paper we propose an image based guiding system based on the extraction of airway centres from intra-operative videos. Such anatomical landmarks are matched to the airway centreline extracted from a pre-planned CT to indicate the best path to the nodule. We present a
feasibility study of our navigation system using simulated bronchoscopic videos and a multi-expert validation of landmarks extraction in 3 intra-operative ultrathin explorations. |
|
|
Address |
Porto; Portugal; February 2017 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
VISAPP |
|
|
Notes |
IAM; 600.096; 600.075; 600.145 |
Approved |
no |
|
|
Call Number |
Admin @ si @ SEB2017 |
Serial |
2943 |
|
Permanent link to this record |
|
|
|
|
Author |
Juan Borrego-Carazo; Carles Sanchez; David Castells; Jordi Carrabina; Debora Gil |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
BronchoPose: an analysis of data and model configuration for vision-based bronchoscopy pose estimation |
Type |
Journal Article |
|
Year |
2023 |
Publication |
Computer Methods and Programs in Biomedicine |
Abbreviated Journal |
CMPB |
|
|
Volume |
228 |
Issue |
|
Pages |
107241 |
|
|
Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
Videobronchoscopy guiding; Deep learning; Architecture optimization; Datasets; Standardized evaluation framework; Pose estimation |
|
|
Abstract |
Vision-based bronchoscopy (VB) models require the registration of the virtual lung model with the frames from the video bronchoscopy to provide effective guidance during the biopsy. The registration can be achieved by either tracking the position and orientation of the bronchoscopy camera or by calibrating its deviation from the pose (position and orientation) simulated in the virtual lung model. Recent advances in neural networks and temporal image processing have provided new opportunities for guided bronchoscopy. However, such progress has been hindered by the lack of comparative experimental conditions.
In the present paper, we share a novel synthetic dataset allowing for a fair comparison of methods. Moreover, this paper investigates several neural network architectures for the learning of temporal information at different levels of subject personalization. In order to improve orientation measurement, we also present a standardized comparison framework and a novel metric for camera orientation learning. Results on the dataset show that the proposed metric and architectures, as well as the standardized conditions, provide notable improvements to current state-of-the-art camera pose estimation in video bronchoscopy. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Elsevier |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
IAM; |
Approved |
no |
|
|
Call Number |
Admin @ si @ BSC2023 |
Serial |
3702 |
|
Permanent link to this record |