|
Records |
Links |
|
Author |
Bogdan Raducanu; Fadi Dornaika |
|
|
Title |
Pose-Invariant Face Recognition in Videos for Human-Machine Interaction |
Type |
Conference Article |
|
Year |
2012 |
Publication |
12th European Conference on Computer Vision |
Abbreviated Journal |
|
|
|
Volume |
7584 |
Issue |
|
Pages |
566.575 |
|
|
Keywords |
|
|
|
Abstract |
Human-machine interaction is a hot topic nowadays in the communities of computer vision and robotics. In this context, face recognition algorithms (used as primary cue for a person’s identity assessment) work well under controlled conditions but degrade significantly when tested in real-world environments. This is mostly due to the difficulty of simultaneously handling variations in illumination, pose, and occlusions. In this paper, we propose a novel approach for robust pose-invariant face recognition for human-robot interaction based on the real-time fitting of a 3D deformable model to input images taken from video sequences. More concrete, our approach generates a rectified face image irrespective with the actual head-pose orientation. Experimental results performed on Honda video database, using several manifold learning techniques, show a distinct advantage of the proposed method over the standard 2D appearance-based snapshot approach. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-33867-0 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ECCVW |
|
|
Notes |
OR;MV |
Approved |
no |
|
|
Call Number |
Admin @ si @ RaD2012e |
Serial |
2182 |
|
Permanent link to this record |
|
|
|
|
Author |
Jose Manuel Alvarez; Y. LeCun; Theo Gevers; Antonio Lopez |
|
|
Title |
Semantic Road Segmentation via Multi-Scale Ensembles of Learned Features |
Type |
Conference Article |
|
Year |
2012 |
Publication |
12th European Conference on Computer Vision – Workshops and Demonstrations |
Abbreviated Journal |
|
|
|
Volume |
7584 |
Issue |
|
Pages |
586-595 |
|
|
Keywords |
road detection |
|
|
Abstract |
Semantic segmentation refers to the process of assigning an object label (e.g., building, road, sidewalk, car, pedestrian) to every pixel in an image. Common approaches formulate the task as a random field labeling problem modeling the interactions between labels by combining local and contextual features such as color, depth, edges, SIFT or HoG. These models are trained to maximize the likelihood of the correct classification given a training set. However, these approaches rely on hand–designed features (e.g., texture, SIFT or HoG) and a higher computational time required in the inference process.
Therefore, in this paper, we focus on estimating the unary potentials of a conditional random field via ensembles of learned features. We propose an algorithm based on convolutional neural networks to learn local features from training data at different scales and resolutions. Then, diversification between these features is exploited using a weighted linear combination. Experiments on a publicly available database show the effectiveness of the proposed method to perform semantic road scene segmentation in still images. The algorithm outperforms appearance based methods and its performance is similar compared to state–of–the–art methods using other sources of information such as depth, motion or stereo. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-33867-0 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ECCVW |
|
|
Notes |
ADAS;ISE |
Approved |
no |
|
|
Call Number |
Admin @ si @ ALG2012; ADAS @ adas |
Serial |
2187 |
|
Permanent link to this record |
|
|
|
|
Author |
Patricia Marquez; Debora Gil; Aura Hernandez-Sabate; Daniel Kondermann |
|
|
Title |
When Is A Confidence Measure Good Enough? |
Type |
Conference Article |
|
Year |
2013 |
Publication |
9th International Conference on Computer Vision Systems |
Abbreviated Journal |
|
|
|
Volume |
7963 |
Issue |
|
Pages |
344-353 |
|
|
Keywords |
Optical flow, confidence measure, performance evaluation |
|
|
Abstract |
Confidence estimation has recently become a hot topic in image processing and computer vision.Yet, several definitions exist of the term “confidence” which are sometimes used interchangeably. This is a position paper, in which we aim to give an overview on existing definitions,
thereby clarifying the meaning of the used terms to facilitate further research in this field. Based on these clarifications, we develop a theory to compare confidence measures with respect to their quality. |
|
|
Address |
St Petersburg; Russia; July 2013 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Link |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-39401-0 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICVS |
|
|
Notes |
IAM;ADAS; 600.044; 600.057; 600.060; 601.145 |
Approved |
no |
|
|
Call Number |
IAM @ iam @ MGH2013a |
Serial |
2218 |
|
Permanent link to this record |
|
|
|
|
Author |
Katerine Diaz; Francesc J. Ferri; W. Diaz |
|
|
Title |
Fast Approximated Discriminative Common Vectors using rank-one SVD updates |
Type |
Conference Article |
|
Year |
2013 |
Publication |
20th International Conference On Neural Information Processing |
Abbreviated Journal |
|
|
|
Volume |
8228 |
Issue |
III |
Pages |
368-375 |
|
|
Keywords |
|
|
|
Abstract |
An efficient incremental approach to the discriminative common vector (DCV) method for dimensionality reduction and classification is presented. The proposal consists of a rank-one update along with an adaptive restriction on the rank of the null space which leads to an approximate but convenient solution. The algorithm can be implemented very efficiently in terms of matrix operations and space complexity, which enables its use in large-scale dynamic application domains. Deep comparative experimentation using publicly available high dimensional image datasets has been carried out in order to properly assess the proposed algorithm against several recent incremental formulations.
K. Diaz-Chito, F.J. Ferri, W. Diaz |
|
|
Address |
Daegu; Korea; November 2013 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-42050-4 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICONIP |
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
Admin @ si @ DFD2013 |
Serial |
2439 |
|
Permanent link to this record |
|
|
|
|
Author |
Oualid M. Benkarim; Petia Radeva; Laura Igual |
|
|
Title |
Label Consistent Multiclass Discriminative Dictionary Learning for MRI Segmentation |
Type |
Conference Article |
|
Year |
2014 |
Publication |
8th Conference on Articulated Motion and Deformable Objects |
Abbreviated Journal |
|
|
|
Volume |
8563 |
Issue |
|
Pages |
138-147 |
|
|
Keywords |
MRI segmentation; sparse representation; discriminative dic- tionary learning; multiclass classication |
|
|
Abstract |
The automatic segmentation of multiple subcortical structures in brain Magnetic Resonance Images (MRI) still remains a challenging task. In this paper, we address this problem using sparse representation and discriminative dictionary learning, which have shown promising results in compression, image denoising and recently in MRI segmentation. Particularly, we use multiclass dictionaries learned from a set of brain atlases to simultaneously segment multiple subcortical structures.
We also impose dictionary atoms to be specialized in one given class using label consistent K-SVD, which can alleviate the bias produced by unbalanced libraries, present when dealing with small structures. The proposed method is compared with other state of the art approaches for the segmentation of the Basal Ganglia of 35 subjects of a public dataset.
The promising results of the segmentation method show the eciency of the multiclass discriminative dictionary learning algorithms in MRI segmentation problems. |
|
|
Address |
Palma de Mallorca; July 2014 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer International Publishing |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-319-08848-8 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
AMDO |
|
|
Notes |
MILAB; OR |
Approved |
no |
|
|
Call Number |
Admin @ si @ BRI2014 |
Serial |
2494 |
|
Permanent link to this record |
|
|
|
|
Author |
Patricia Marquez; H. Kause; A. Fuster; Aura Hernandez-Sabate; L. Florack; Debora Gil; Hans van Assen |
|
|
Title |
Factors Affecting Optical Flow Performance in Tagging Magnetic Resonance Imaging |
Type |
Conference Article |
|
Year |
2014 |
Publication |
17th International Conference on Medical Image Computing and Computer Assisted Intervention |
Abbreviated Journal |
|
|
|
Volume |
8896 |
Issue |
|
Pages |
231-238 |
|
|
Keywords |
Optical flow; Performance Evaluation; Synthetic Database; ANOVA; Tagging Magnetic Resonance Imaging |
|
|
Abstract |
Changes in cardiac deformation patterns are correlated with cardiac pathologies. Deformation can be extracted from tagging Magnetic Resonance Imaging (tMRI) using Optical Flow (OF) techniques. For applications of OF in a clinical setting it is important to assess to what extent the performance of a particular OF method is stable across dierent clinical acquisition artifacts. This paper presents a statistical validation framework, based on ANOVA, to assess the motion and appearance factors that have the largest in uence on OF accuracy drop.
In order to validate this framework, we created a database of simulated tMRI data including the most common artifacts of MRI and test three dierent OF methods, including HARP. |
|
|
Address |
Boston; USA; September 2014 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer International Publishing |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-319-14677-5 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
STACOM |
|
|
Notes |
IAM; ADAS; 600.060; 601.145; 600.076; 600.075 |
Approved |
no |
|
|
Call Number |
Admin @ si @ MKF2014 |
Serial |
2495 |
|
Permanent link to this record |
|
|
|
|
Author |
Jorge Bernal; Debora Gil; Carles Sanchez; F. Javier Sanchez |
|
|
Title |
Discarding Non Informative Regions for Efficient Colonoscopy Image Analysis |
Type |
Conference Article |
|
Year |
2014 |
Publication |
1st MICCAI Workshop on Computer-Assisted and Robotic Endoscopy |
Abbreviated Journal |
|
|
|
Volume |
8899 |
Issue |
|
Pages |
1-10 |
|
|
Keywords |
Image Segmentation; Polyps, Colonoscopy; Valley Information; Energy Maps |
|
|
Abstract |
In this paper we present a novel polyp region segmentation method for colonoscopy videos. Our method uses valley information associated to polyp boundaries in order to provide an initial segmentation. This first segmentation is refined to eliminate boundary discontinuities caused by image artifacts or other elements of the scene. Experimental results over a publicly annotated database show that our method outperforms both general and specific segmentation methods by providing more accurate regions rich in polyp content. We also prove how image preprocessing is needed to improve final polyp region segmentation. |
|
|
Address |
Boston; USA; September 2014 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer International Publishing |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-319-13409-3 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
CARE |
|
|
Notes |
MV; IAM; 600.044; 600.047; 600.060; 600.075 |
Approved |
no |
|
|
Call Number |
Admin @ si @ BGS2014b |
Serial |
2503 |
|
Permanent link to this record |
|
|
|
|
Author |
Sergio Escalera; Xavier Baro; Jordi Gonzalez; Miguel Angel Bautista; Meysam Madadi; Miguel Reyes; Victor Ponce; Hugo Jair Escalante; Jaime Shotton; Isabelle Guyon |
|
|
Title |
ChaLearn Looking at People Challenge 2014: Dataset and Results |
Type |
Conference Article |
|
Year |
2014 |
Publication |
ECCV Workshop on ChaLearn Looking at People |
Abbreviated Journal |
|
|
|
Volume |
8925 |
Issue |
|
Pages |
459-473 |
|
|
Keywords |
Human Pose Recovery; Behavior Analysis; Action and in- teractions; Multi-modal gestures; recognition |
|
|
Abstract |
This paper summarizes the ChaLearn Looking at People 2014 challenge data and the results obtained by the participants. The competition was split into three independent tracks: human pose recovery from RGB data, action and interaction recognition from RGB data sequences, and multi-modal gesture recognition from RGB-Depth sequences. For all the tracks, the goal was to perform user-independent recognition in sequences of continuous images using the overlapping Jaccard index as the evaluation measure. In this edition of the ChaLearn challenge, two large novel data sets were made publicly available and the Microsoft Codalab platform were used to manage the competition. Outstanding results were achieved in the three challenge tracks, with accuracy results of 0.20, 0.50, and 0.85 for pose recovery, action/interaction recognition, and multi-modal gesture recognition, respectively. |
|
|
Address |
|
|
|
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 |
ECCVW |
|
|
Notes |
HuPBA; ISE; 600.063;MV |
Approved |
no |
|
|
Call Number |
Admin @ si @ EBG2014 |
Serial |
2529 |
|
Permanent link to this record |
|
|
|
|
Author |
Xavier Perez Sala; Fernando De la Torre; Laura Igual; Sergio Escalera; Cecilio Angulo |
|
|
Title |
Subspace Procrustes Analysis |
Type |
Conference Article |
|
Year |
2014 |
Publication |
ECCV Workshop on ChaLearn Looking at People |
Abbreviated Journal |
|
|
|
Volume |
8925 |
Issue |
|
Pages |
654-668 |
|
|
Keywords |
|
|
|
Abstract |
Procrustes Analysis (PA) has been a popular technique to align and build 2-D statistical models of shapes. Given a set of 2-D shapes PA is applied to remove rigid transformations. Then, a non-rigid 2-D model is computed by modeling (e.g., PCA) the residual. Although PA has been widely used, it has several limitations for modeling 2-D shapes: occluded landmarks and missing data can result in local minima solutions, and there is no guarantee that the 2-D shapes provide a uniform sampling of the 3-D space of rotations for the object. To address previous issues, this paper proposes Subspace PA (SPA). Given several instances of a 3-D object, SPA computes the mean and a 2-D subspace that can simultaneously model all rigid and non-rigid deformations of the 3-D object. We propose a discrete (DSPA) and continuous (CSPA) formulation for SPA, assuming that 3-D samples of an object are provided. DSPA extends the traditional PA, and produces unbiased 2-D models by uniformly sampling dierent views of the 3-D object. CSPA provides a continuous approach to uniformly sample the space of 3-D rotations, being more ecient in space and time. Experiments using SPA to learn 2-D models of bodies from motion capture data illustrate the benets of our approach. |
|
|
Address |
|
|
|
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 |
ECCVW |
|
|
Notes |
OR; HuPBA;MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ PTI2014 |
Serial |
2539 |
|
Permanent link to this record |
|
|
|
|
Author |
Eloi Puertas; Miguel Angel Bautista; Daniel Sanchez; Sergio Escalera; Oriol Pujol |
|
|
Title |
Learning to Segment Humans by Stacking their Body Parts, |
Type |
Conference Article |
|
Year |
2014 |
Publication |
ECCV Workshop on ChaLearn Looking at People |
Abbreviated Journal |
|
|
|
Volume |
8925 |
Issue |
|
Pages |
685-697 |
|
|
Keywords |
Human body segmentation; Stacked Sequential Learning |
|
|
Abstract |
Human segmentation in still images is a complex task due to the wide range of body poses and drastic changes in environmental conditions. Usually, human body segmentation is treated in a two-stage fashion. First, a human body part detection step is performed, and then, human part detections are used as prior knowledge to be optimized by segmentation strategies. In this paper, we present a two-stage scheme based on Multi-Scale Stacked Sequential Learning (MSSL). We define an extended feature set by stacking a multi-scale decomposition of body
part likelihood maps. These likelihood maps are obtained in a first stage
by means of a ECOC ensemble of soft body part detectors. In a second stage, contextual relations of part predictions are learnt by a binary classifier, obtaining an accurate body confidence map. The obtained confidence map is fed to a graph cut optimization procedure to obtain the final segmentation. Results show improved segmentation when MSSL is included in the human segmentation pipeline. |
|
|
Address |
|
|
|
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 |
ECCVW |
|
|
Notes |
HuPBA;MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ PBS2014 |
Serial |
2553 |
|
Permanent link to this record |
|
|
|
|
Author |
Francesco Brughi; Debora Gil; Llorenç Badiella; Eva Jove Casabella; Oriol Ramos Terrades |
|
|
Title |
Exploring the impact of inter-query variability on the performance of retrieval systems |
Type |
Conference Article |
|
Year |
2014 |
Publication |
11th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
8814 |
Issue |
|
Pages |
413–420 |
|
|
Keywords |
|
|
|
Abstract |
This paper introduces a framework for evaluating the performance of information retrieval systems. Current evaluation metrics provide an average score that does not consider performance variability across the query set. In this manner, conclusions lack of any statistical significance, yielding poor inference to cases outside the query set and possibly unfair comparisons. We propose to apply statistical methods in order to obtain a more informative measure for problems in which different query classes can be identified. In this context, we assess the performance variability on two levels: overall variability across the whole query set and specific query class-related variability. To this end, we estimate confidence bands for precision-recall curves, and we apply ANOVA in order to assess the significance of the performance across different query classes. |
|
|
Address |
Algarve; Portugal; October 2014 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer International Publishing |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-319-11757-7 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICIAR |
|
|
Notes |
IAM; DAG; 600.060; 600.061; 600.077; 600.075 |
Approved |
no |
|
|
Call Number |
Admin @ si @ BGB2014 |
Serial |
2559 |
|
Permanent link to this record |
|
|
|
|
Author |
Marcelo D. Pistarelli; Angel Sappa; Ricardo Toledo |
|
|
Title |
Multispectral Stereo Image Correspondence |
Type |
Conference Article |
|
Year |
2013 |
Publication |
15th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
|
|
|
Volume |
8048 |
Issue |
|
Pages |
217-224 |
|
|
Keywords |
|
|
|
Abstract |
This paper presents a novel multispectral stereo image correspondence approach. It is evaluated using a stereo rig constructed with a visible spectrum camera and a long wave infrared spectrum camera. The novelty of the proposed approach lies on the usage of Hough space as a correspondence search domain. In this way it avoids searching for correspondence in the original multispectral image domains, where information is low correlated, and a common domain is used. The proposed approach is intended to be used in outdoor urban scenarios, where images contain large amount of edges. These edges are used as distinctive characteristics for the matching in the Hough space. Experimental results are provided showing the validity of the proposed approach. |
|
|
Address |
York; uk; August 2013 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-40245-6 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
CAIP |
|
|
Notes |
ADAS; 600.055 |
Approved |
no |
|
|
Call Number |
Admin @ si @ PST2013 |
Serial |
2561 |
|
Permanent link to this record |
|
|
|
|
Author |
Gioacchino Vino; Angel Sappa |
|
|
Title |
Revisiting Harris Corner Detector Algorithm: a Gradual Thresholding Approach |
Type |
Conference Article |
|
Year |
2013 |
Publication |
10th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
7950 |
Issue |
|
Pages |
354-363 |
|
|
Keywords |
|
|
|
Abstract |
This paper presents an adaptive thresholding approach intended to increase the number of detected corners, while reducing the amount of those ones corresponding to noisy data. The proposed approach works by using the classical Harris corner detector algorithm and overcome the difficulty in finding a general threshold that work well for all the images in a given data set by proposing a novel adaptive thresholding scheme. Initially, two thresholds are used to discern between strong corners and flat regions. Then, a region based criteria is used to discriminate between weak corners and noisy points in the midway interval. Experimental results show that the proposed approach has a better capability to reject false corners and, at the same time, to detect weak ones. Comparisons with the state of the art are provided showing the validity of the proposed approach. |
|
|
Address |
Póvoa de Varzim; Portugal; June 2013 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-39093-7 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICIAR |
|
|
Notes |
ADAS; 600.055 |
Approved |
no |
|
|
Call Number |
Admin @ si @ ViS2013 |
Serial |
2562 |
|
Permanent link to this record |
|
|
|
|
Author |
Marc Bolaños; Maite Garolera; Petia Radeva |
|
|
Title |
Object Discovery using CNN Features in Egocentric Videos |
Type |
Conference Article |
|
Year |
2015 |
Publication |
Pattern Recognition and Image Analysis, Proceedings of 7th Iberian Conference , ibPRIA 2015 |
Abbreviated Journal |
|
|
|
Volume |
9117 |
Issue |
|
Pages |
67-74 |
|
|
Keywords |
Object discovery; Egocentric videos; Lifelogging; CNN |
|
|
Abstract |
Lifelogging devices based on photo/video are spreading faster everyday. This growth can represent great benefits to develop methods for extraction of meaningful information about the user wearing the device and his/her environment. In this paper, we propose a semi-supervised strategy for easily discovering objects relevant to the person wearing a first-person camera. The egocentric video sequence acquired by the camera, uses both the appearance extracted by means of a deep convolutional neural network and an object refill methodology that allow to discover objects even in case of small amount of object appearance in the collection of images. We validate our method on a sequence of 1000 egocentric daily images and obtain results with an F-measure of 0.5, 0.17 better than the state of the art approach. |
|
|
Address |
Santiago de Compostela; España; June 2015 |
|
|
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 |
0302-9743 |
ISBN |
978-3-319-19389-2 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
IbPRIA |
|
|
Notes |
MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ BGR2015 |
Serial |
2596 |
|
Permanent link to this record |
|
|
|
|
Author |
Estefania Talavera; Mariella Dimiccoli; Marc Bolaños; Maedeh Aghaei; Petia Radeva |
|
|
Title |
R-clustering for egocentric video segmentation |
Type |
Conference Article |
|
Year |
2015 |
Publication |
Pattern Recognition and Image Analysis, Proceedings of 7th Iberian Conference , ibPRIA 2015 |
Abbreviated Journal |
|
|
|
Volume |
9117 |
Issue |
|
Pages |
327-336 |
|
|
Keywords |
Temporal video segmentation; Egocentric videos; Clustering |
|
|
Abstract |
In this paper, we present a new method for egocentric video temporal segmentation based on integrating a statistical mean change detector and agglomerative clustering(AC) within an energy-minimization framework. Given the tendency of most AC methods to oversegment video sequences when clustering their frames, we combine the clustering with a concept drift detection technique (ADWIN) that has rigorous guarantee of performances. ADWIN serves as a statistical upper bound for the clustering-based video segmentation. We integrate both techniques in an energy-minimization framework that serves to disambiguate the decision of both techniques and to complete the segmentation taking into account the temporal continuity of video frames descriptors. We present experiments over egocentric sets of more than 13.000 images acquired with different wearable cameras, showing that our method outperforms state-of-the-art clustering methods. |
|
|
Address |
Santiago de Compostela; España; June 2015 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer International Publishing |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-319-19389-2 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
IbPRIA |
|
|
Notes |
MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ TDB2015 |
Serial |
2597 |
|
Permanent link to this record |