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Author |
A. Sanfeliu; Juan J. Villanueva |
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Title |
An approach of visual motion analysis |
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Journal Article |
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2005 |
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Pattern Recognition Letters |
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PRL |
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26 |
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3 |
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355–368 |
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IF: 1.138 |
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no |
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ISE @ ise @ SaV2005 |
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561 |
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Author |
Jaume Amores; Petia Radeva |
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Title |
Registration and Retrieval of Highly Elastic Bodies using Contextual Information |
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Journal Article |
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Year |
2005 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
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Volume |
26 |
Issue |
11 |
Pages |
1720–1731 |
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IF: 1.138 |
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ADAS;MILAB |
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ADAS @ adas @ AmR2005b |
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592 |
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Author |
B. Gotschy; Matthias S. Keil; H. Klos; I. Rystau |
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Title |
Transition from static to dynamic Jahn-Teller distortion in (P(C6 H5)4)2 C60| |
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Year |
1994 |
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Solid State Communications |
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92 |
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12 |
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935-938 |
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Admin @ si @ GKK1994 |
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631 |
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Author |
Oriol Ramos Terrades; Ernest Valveny |
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Title |
A new use of the ridgelets transform for describing linear singularities in images |
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Journal Article |
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Year |
2006 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
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Volume |
27 |
Issue |
6 |
Pages |
587–596 |
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DAG |
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DAG @ dag @ RaV2006a |
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635 |
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Author |
Jaume Amores; N. Sebe; Petia Radeva |
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Title |
Boosting the distance estimation: Application to the K-Nearest Neighbor Classifier |
Type |
Journal Article |
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Year |
2006 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
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Volume |
27 |
Issue |
3 |
Pages |
201–209 |
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ADAS;MILAB |
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no |
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ADAS @ adas @ ASR2006 |
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643 |
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Author |
Fernando Vilariño; Ludmila I. Kuncheva; Petia Radeva |
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Title |
ROC curves and video analysis optimization in intestinal capsule endoscopy |
Type |
Journal Article |
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Year |
2006 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
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Volume |
27 |
Issue |
8 |
Pages |
875–881 |
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Keywords |
ROC curves; Classification; Classifiers ensemble; Detection of intestinal contractions; Imbalanced classes; Wireless capsule endoscopy |
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Abstract |
Wireless capsule endoscopy involves inspection of hours of video material by a highly qualified professional. Time episodes corresponding to intestinal contractions, which are of interest to the physician constitute about 1% of the video. The problem is to label automatically time episodes containing contractions so that only a fraction of the video needs inspection. As the classes of contraction and non-contraction images in the video are largely imbalanced, ROC curves are used to optimize the trade-off between false positive and false negative rates. Classifier ensemble methods and simple classifiers were examined. Our results reinforce the claims from recent literature that classifier ensemble methods specifically designed for imbalanced problems have substantial advantages over simple classifiers and standard classifier ensembles. By using ROC curves with the bagging ensemble method the inspection time can be drastically reduced at the expense of a small fraction of missed contractions. |
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800 |
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Notes |
MILAB;MV;SIAI |
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no |
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Call Number |
BCNPCL @ bcnpcl @ VKR2006; IAM @ iam @ VKR2006 |
Serial |
647 |
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Author |
Angel Sappa; David Geronimo; Fadi Dornaika; Antonio Lopez |
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Title |
On-board camera extrinsic parameter estimation |
Type |
Journal Article |
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Year |
2006 |
Publication |
Electronics Letters |
Abbreviated Journal |
EL |
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Volume |
42 |
Issue |
13 |
Pages |
745–746 |
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Abstract |
An efficient technique for real-time estimation of camera extrinsic parameters is presented. It is intended to be used on on-board vision systems for driving assistance applications. The proposed technique is based on the use of a commercial stereo vision system that does not need any visual feature extraction. |
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IEE |
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ADAS |
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no |
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Call Number |
ADAS @ adas @ SGD2006a |
Serial |
655 |
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Author |
Xavier Otazu; Oriol Pujol |
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Title |
Wavelet based approach to cluster analysis. Application on low dimensional data sets |
Type |
Journal Article |
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Year |
2006 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
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Volume |
27 |
Issue |
14 |
Pages |
1590–1605 |
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Notes |
MILAB; CIC; HuPBA |
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no |
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Call Number |
BCNPCL @ bcnpcl @ OtP2006 |
Serial |
658 |
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Author |
Jaume Amores |
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Title |
Multiple Instance Classification: review, taxonomy and comparative study |
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Journal Article |
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Year |
2013 |
Publication |
Artificial Intelligence |
Abbreviated Journal |
AI |
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Volume |
201 |
Issue |
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Pages |
81-105 |
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Keywords |
Multi-instance learning; Codebook; Bag-of-Words |
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Abstract |
Multiple Instance Learning (MIL) has become an important topic in the pattern recognition community, and many solutions to this problemhave been proposed until now. Despite this fact, there is a lack of comparative studies that shed light into the characteristics and behavior of the different methods. In this work we provide such an analysis focused on the classification task (i.e.,leaving out other learning tasks such as regression). In order to perform our study, we implemented
fourteen methods grouped into three different families. We analyze the performance of the approaches across a variety of well-known databases, and we also study their behavior in synthetic scenarios in order to highlight their characteristics. As a result of this analysis, we conclude that methods that extract global bag-level information show a clearly superior performance in general. In this sense, the analysis permits us to understand why some types of methods are more successful than others, and it permits us to establish guidelines in the design of new MIL
methods. |
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Elsevier Science Publishers Ltd. Essex, UK |
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0004-3702 |
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Notes |
ADAS; 601.042; 600.057 |
Approved |
no |
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Call Number |
Admin @ si @ Amo2013 |
Serial |
2273 |
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Permanent link to this record |
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Author |
Jaume Amores |
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Title |
MILDE: multiple instance learning by discriminative embedding |
Type |
Journal Article |
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Year |
2015 |
Publication |
Knowledge and Information Systems |
Abbreviated Journal |
KAIS |
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Volume |
42 |
Issue |
2 |
Pages |
381-407 |
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Keywords |
Multi-instance learning; Codebook; Bag of words |
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Abstract |
While the objective of the standard supervised learning problem is to classify feature vectors, in the multiple instance learning problem, the objective is to classify bags, where each bag contains multiple feature vectors. This represents a generalization of the standard problem, and this generalization becomes necessary in many real applications such as drug activity prediction, content-based image retrieval, and others. While the existing paradigms are based on learning the discriminant information either at the instance level or at the bag level, we propose to incorporate both levels of information. This is done by defining a discriminative embedding of the original space based on the responses of cluster-adapted instance classifiers. Results clearly show the advantage of the proposed method over the state of the art, where we tested the performance through a variety of well-known databases that come from real problems, and we also included an analysis of the performance using synthetically generated data. |
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Springer London |
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ISSN |
0219-1377 |
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Notes |
ADAS; 601.042; 600.057; 600.076 |
Approved |
no |
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Call Number |
Admin @ si @ Amo2015 |
Serial |
2383 |
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Author |
Albert Gordo; Florent Perronnin; Yunchao Gong; Svetlana Lazebnik |
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Title |
Asymmetric Distances for Binary Embeddings |
Type |
Journal Article |
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Year |
2014 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence |
Abbreviated Journal |
TPAMI |
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Volume |
36 |
Issue |
1 |
Pages |
33-47 |
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Abstract |
In large-scale query-by-example retrieval, embedding image signatures in a binary space offers two benefits: data compression and search efficiency. While most embedding algorithms binarize both query and database signatures, it has been noted that this is not strictly a requirement. Indeed, asymmetric schemes which binarize the database signatures but not the query still enjoy the same two benefits but may provide superior accuracy. In this work, we propose two general asymmetric distances which are applicable to a wide variety of embedding techniques including Locality Sensitive Hashing (LSH), Locality Sensitive Binary Codes (LSBC), Spectral Hashing (SH), PCA Embedding (PCAE), PCA Embedding with random rotations (PCAE-RR), and PCA Embedding with iterative quantization (PCAE-ITQ). We experiment on four public benchmarks containing up to 1M images and show that the proposed asymmetric distances consistently lead to large improvements over the symmetric Hamming distance for all binary embedding techniques. |
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0162-8828 |
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DAG; 600.045; 605.203; 600.077 |
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no |
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Admin @ si @ GPG2014 |
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2272 |
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Author |
Fadi Dornaika; Angel Sappa |
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Title |
Rigid and Non-rigid Face Motion Tracking by Aligning Texture Maps and Stereo 3D Models |
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Journal Article |
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Year |
2007 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
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Volume |
28 |
Issue |
15 |
Pages |
2116-2126 |
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ADAS |
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ADAS @ adas @ DoS2007c |
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877 |
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Author |
Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez |
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Title |
Rank Estimation in 3D Multibody Motion Segmentation |
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Journal Article |
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Year |
2008 |
Publication |
Electronic Letters |
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44 |
Issue |
4 |
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279-280 |
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Abstract |
A novel technique for rank estimation in 3D multibody motion segmentation is proposed. It is based on the study of the frequency spectra of moving rigid objects and does not use or assume a prior knowledge of the objects contained in the scene (i.e. number of objects and motion). The significance of rank estimation on multibody motion segmentation results is shown by using two motion segmentation algorithms over both synthetic and real data. |
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ADAS |
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ADAS @ adas @ JSL2008a |
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939 |
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Author |
Joan Serrat; Ferran Diego; Felipe Lumbreras; Jose Manuel Alvarez; Antonio Lopez; C. Elvira |
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Title |
Dynamic Comparison of Headlights |
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Journal Article |
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Year |
2008 |
Publication |
Journal of Automobile Engineering |
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222 |
Issue |
5 |
Pages |
643–656 |
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video alignment |
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ADAS |
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no |
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ADAS @ adas @ SDL2008a |
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958 |
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Author |
Francisco Javier Orozco; Xavier Roca; Jordi Gonzalez |
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Title |
Real-Time Gaze Tracking with Appearance-Based Models |
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Journal Article |
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Year |
2008 |
Publication |
Machine Vision Applications |
Abbreviated Journal |
MVAP |
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Volume |
20 |
Issue |
6 |
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353-364 |
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Keywords Eyelid and iris tracking, Appearance models, Blinking, Iris saccade, Real-time gaze tracking |
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Abstract |
Psychological evidence has emphasized the importance of eye gaze analysis in human computer interaction and emotion interpretation. To this end, current image analysis algorithms take into consideration eye-lid and iris motion detection using colour information and edge detectors. However, eye movement is fast and and hence difficult to use to obtain a precise and robust tracking. Instead, our
method proposed to describe eyelid and iris movements as continuous variables using appearance-based tracking. This approach combines the strengths of adaptive appearance models, optimization methods and backtracking techniques.Thus,
in the proposed method textures are learned on-line from near frontal images and illumination changes, occlusions and fast movements are managed. The method achieves real-time performance by combining two appearance-based trackers to a
backtracking algorithm for eyelid estimation and another for iris estimation. These contributions represent a significant advance towards a reliable gaze motion description for HCI and expression analysis, where the strength of complementary
methodologies are combined to avoid using high quality images, colour information, texture training, camera settings and other time-consuming processes. |
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ISE |
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no |
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Call Number |
ISE @ ise @ ORG2008 |
Serial |
972 |
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