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Author |
Andreas Møgelmose; Chris Bahnsen; Thomas B. Moeslund; Albert Clapes; Sergio Escalera |
![download PDF file pdf](img/file_PDF.gif)
![find book details (via ISBN) isbn](img/isbn.gif)
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Title |
Tri-modal Person Re-identification with RGB, Depth and Thermal Features |
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Conference Article |
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Year |
2013 |
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9th IEEE Workshop on Perception beyond the visible Spectrum, Computer Vision and Pattern Recognition |
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301-307 |
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Person re-identification is about recognizing people who have passed by a sensor earlier. Previous work is mainly based on RGB data, but in this work we for the first time present a system where we combine RGB, depth, and thermal data for re-identification purposes. First, from each of the three modalities, we obtain some particular features: from RGB data, we model color information from different regions of the body, from depth data, we compute different soft body biometrics, and from thermal data, we extract local structural information. Then, the three information types are combined in a joined classifier. The tri-modal system is evaluated on a new RGB-D-T dataset, showing successful results in re-identification scenarios. |
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Address ![sorted by Address field, descending order (down)](img/sort_desc.gif) |
Portland; oregon; June 2013 |
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978-0-7695-4990-3 |
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CVPRW |
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HUPBA;MILAB |
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no |
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Admin @ si @ MBM2013 |
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2253 |
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Author |
David Vazquez; Jiaolong Xu; Sebastian Ramos; Antonio Lopez; Daniel Ponsa |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Weakly Supervised Automatic Annotation of Pedestrian Bounding Boxes |
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Conference Article |
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Year |
2013 |
Publication |
CVPR Workshop on Ground Truth – What is a good dataset? |
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706 - 711 |
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Pedestrian Detection; Domain Adaptation |
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Among the components of a pedestrian detector, its trained pedestrian classifier is crucial for achieving the desired performance. The initial task of the training process consists in collecting samples of pedestrians and background, which involves tiresome manual annotation of pedestrian bounding boxes (BBs). Thus, recent works have assessed the use of automatically collected samples from photo-realistic virtual worlds. However, learning from virtual-world samples and testing in real-world images may suffer the dataset shift problem. Accordingly, in this paper we assess an strategy to collect samples from the real world and retrain with them, thus avoiding the dataset shift, but in such a way that no BBs of real-world pedestrians have to be provided. In particular, we train a pedestrian classifier based on virtual-world samples (no human annotation required). Then, using such a classifier we collect pedestrian samples from real-world images by detection. After, a human oracle rejects the false detections efficiently (weak annotation). Finally, a new classifier is trained with the accepted detections. We show that this classifier is competitive with respect to the counterpart trained with samples collected by manually annotating hundreds of pedestrian BBs. |
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Address ![sorted by Address field, descending order (down)](img/sort_desc.gif) |
Portland; Oregon; June 2013 |
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IEEE |
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English |
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English |
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ADAS; 600.054; 600.057; 601.217 |
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ADAS @ adas @ VXR2013a |
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2219 |
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Jiaolong Xu; David Vazquez; Sebastian Ramos; Antonio Lopez; Daniel Ponsa |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Adapting a Pedestrian Detector by Boosting LDA Exemplar Classifiers |
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Conference Article |
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Year |
2013 |
Publication |
CVPR Workshop on Ground Truth – What is a good dataset? |
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688 - 693 |
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Pedestrian Detection; Domain Adaptation |
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Training vision-based pedestrian detectors using synthetic datasets (virtual world) is a useful technique to collect automatically the training examples with their pixel-wise ground truth. However, as it is often the case, these detectors must operate in real-world images, experiencing a significant drop of their performance. In fact, this effect also occurs among different real-world datasets, i.e. detectors' accuracy drops when the training data (source domain) and the application scenario (target domain) have inherent differences. Therefore, in order to avoid this problem, it is required to adapt the detector trained with synthetic data to operate in the real-world scenario. In this paper, we propose a domain adaptation approach based on boosting LDA exemplar classifiers from both virtual and real worlds. We evaluate our proposal on multiple real-world pedestrian detection datasets. The results show that our method can efficiently adapt the exemplar classifiers from virtual to real world, avoiding drops in average precision over the 15%. |
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Address ![sorted by Address field, descending order (down)](img/sort_desc.gif) |
Portland; oregon; June 2013 |
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ADAS; 600.054; 600.057; 601.217 |
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yes |
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XVR2013; ADAS @ adas @ xvr2013a |
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2220 |
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Author |
Ivan Huerta; Ariel Amato; Jordi Gonzalez; Juan J. Villanueva |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Fusing Edge Cues to Handle Colour Problems in Image Segmentation |
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Book Chapter |
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Year |
2008 |
Publication |
Articulated Motion and Deformable Objects, 5th International Conference |
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5098 |
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279–288 |
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Address ![sorted by Address field, descending order (down)](img/sort_desc.gif) |
Port d'Andratx (Mallorca) |
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AMDO |
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ISE |
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no |
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ISE @ ise @ HAG2008 |
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973 |
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Author |
Pau Baiget; Xavier Roca; Jordi Gonzalez |
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Title |
Autonomous Virtual Agents for Performance Evaluation of Tracking Algorithms |
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Book Chapter |
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Year |
2008 |
Publication |
Articulated Motion and Deformable Objects, 5th International Conference AMDO 2008, |
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5098 |
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299-308 |
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Address ![sorted by Address field, descending order (down)](img/sort_desc.gif) |
Port d'Andratx (Mallorca) |
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ISE |
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no |
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ISE @ ise @ BRG2008 |
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974 |
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Author |
Bhaskar Chakraborty; Marco Pedersoli; Jordi Gonzalez |
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Title |
View-Invariant Human Action Detection using Component-Wise HMM of Body Parts |
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Book Chapter |
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2008 |
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Articulated Motion and Deformable Objects, 5th International Conference |
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5098 |
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208–217 |
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Address ![sorted by Address field, descending order (down)](img/sort_desc.gif) |
Port d'Andratx (Mallorca) |
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AMDO |
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ISE |
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no |
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ISE @ ise @ CPG2008 |
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975 |
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Author |
Olivier Lefebvre; Pau Riba; Charles Fournier; Alicia Fornes; Josep Llados; Rejean Plamondon; Jules Gagnon-Marchand |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Monitoring neuromotricity on-line: a cloud computing approach |
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Conference Article |
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Year |
2015 |
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17th Conference of the International Graphonomics Society IGS2015 |
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The goal of our experiment is to develop a useful and accessible tool that can be used to evaluate a patient's health by analyzing handwritten strokes. We use a cloud computing approach to analyze stroke data sampled on a commercial tablet working on the Android platform and a distant server to perform complex calculations using the Delta and Sigma lognormal algorithms. A Google Drive account is used to store the data and to ease the development of the project. The communication between the tablet, the cloud and the server is encrypted to ensure biomedical information confidentiality. Highly parameterized biomedical tests are implemented on the tablet as well as a free drawing test to evaluate the validity of the data acquired by the first test compared to the second one. A blurred shape model descriptor pattern recognition algorithm is used to classify the data obtained by the free drawing test. The functions presented in this paper are still currently under development and other improvements are needed before launching the application in the public domain. |
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Address ![sorted by Address field, descending order (down)](img/sort_desc.gif) |
Pointe-à-Pitre; Guadeloupe; June 2015 |
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IGS |
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DAG; 600.077 |
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no |
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Admin @ si @ LRF2015 |
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2617 |
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Author |
Esteve Cervantes; Long Long Yu; Andrew Bagdanov; Marc Masana; Joost Van de Weijer |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Hierarchical Part Detection with Deep Neural Networks |
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Conference Article |
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2016 |
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23rd IEEE International Conference on Image Processing |
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Object Recognition; Part Detection; Convolutional Neural Networks |
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Part detection is an important aspect of object recognition. Most approaches apply object proposals to generate hundreds of possible part bounding box candidates which are then evaluated by part classifiers. Recently several methods have investigated directly regressing to a limited set of bounding boxes from deep neural network representation. However, for object parts such methods may be unfeasible due to their relatively small size with respect to the image. We propose a hierarchical method for object and part detection. In a single network we first detect the object and then regress to part location proposals based only on the feature representation inside the object. Experiments show that our hierarchical approach outperforms a network which directly regresses the part locations. We also show that our approach obtains part detection accuracy comparable or better than state-of-the-art on the CUB-200 bird and Fashionista clothing item datasets with only a fraction of the number of part proposals. |
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Address ![sorted by Address field, descending order (down)](img/sort_desc.gif) |
Phoenix; Arizona; USA; September 2016 |
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ICIP |
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LAMP; 600.106 |
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no |
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Admin @ si @ CLB2016 |
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2762 |
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Author |
Sounak Dey; Anjan Dutta; Suman Ghosh; Ernest Valveny; Josep Llados |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Aligning Salient Objects to Queries: A Multi-modal and Multi-object Image Retrieval Framework |
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Conference Article |
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Year |
2018 |
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14th Asian Conference on Computer Vision |
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In this paper we propose an approach for multi-modal image retrieval in multi-labelled images. A multi-modal deep network architecture is formulated to jointly model sketches and text as input query modalities into a common embedding space, which is then further aligned with the image feature space. Our architecture also relies on a salient object detection through a supervised LSTM-based visual attention model learned from convolutional features. Both the alignment between the queries and the image and the supervision of the attention on the images are obtained by generalizing the Hungarian Algorithm using different loss functions. This permits encoding the object-based features and its alignment with the query irrespective of the availability of the co-occurrence of different objects in the training set. We validate the performance of our approach on standard single/multi-object datasets, showing state-of-the art performance in every dataset. |
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Address ![sorted by Address field, descending order (down)](img/sort_desc.gif) |
Perth; Australia; December 2018 |
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ACCV |
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DAG; 600.097; 600.121; 600.129 |
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no |
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Admin @ si @ DDG2018a |
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3151 |
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Author |
Oriol Pujol; Petia Radeva |
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Title |
Optimal extension of Error Correcting Output Codes |
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Miscellaneous |
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2006 |
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Address ![sorted by Address field, descending order (down)](img/sort_desc.gif) |
Perpignan (France) |
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MILAB;HuPBA |
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no |
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BCNPCL @ bcnpcl @ EPR2006d |
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695 |
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Author |
Panagiota Spyridonos; Fernando Vilariño; Jordi Vitria; Petia Radeva; Fernando Azpiroz; Juan Malagelada |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Device, system and method for automatic detection of contractile activity in an image frame |
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Patent |
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2011 |
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US 2011/0044515 A1 |
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A device, system and method for automatic detection of contractile activity of a body lumen in an image frame is provided, wherein image frames during contractile activity are captured and/or image frames including contractile activity are automatically detected, such as through pattern recognition and/or feature extraction to trace image frames including contractions, e.g., with wrinkle patterns. A manual procedure of annotation of contractions, e.g. tonic contractions in capsule endoscopy, may consist of the visualization of the whole video by a specialist, and the labeling of the contraction frames. Embodiments of the present invention may be suitable for implementation in an in vivo imaging system. |
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Address ![sorted by Address field, descending order (down)](img/sort_desc.gif) |
Pearl Cohen Zedek Latzer, LLP, 1500 Broadway 12th Floor, New York (NY) 10036 (US) |
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US Patent Office |
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MV;OR;MILAB;SIAI |
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IAM @ iam @ SVV2011 |
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1701 |
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Fernando Vilariño; Panagiota Spyridonos; Petia Radeva; Jordi Vitria; Fernando Azpiroz; Juan Malagelada |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Device, system and method for measurement and analysis of contractile activity |
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Patent |
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2009 |
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US 2009/0202117 A1 |
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A method and system for determining intestinal dysfunction condition are provided by classifying and analyzing image frames captured in-vivo. The method and system also relate to the detection of contractile activity in intestinal tracts, to automatic detection of video image frames taken in the gastrointestinal tract including contractile activity, and more particularly to measurement and analysis of contractile activity of the GI tract based on image intensity of in vivo image data. |
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Address ![sorted by Address field, descending order (down)](img/sort_desc.gif) |
Pearl Cohen Zedek Latzer |
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800 |
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MV;OR;MILAB;SIAI |
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IAM @ iam @ VSR2009 |
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1704 |
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Author |
Gioacchino Vino; Angel Sappa |
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Title |
Revisiting Harris Corner Detector Algorithm: a Gradual Thresholding Approach |
Type |
Conference Article |
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2013 |
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10th International Conference on Image Analysis and Recognition |
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7950 |
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354-363 |
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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. |
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Address ![sorted by Address field, descending order (down)](img/sort_desc.gif) |
Póvoa de Varzim; Portugal; June 2013 |
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Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-39093-7 |
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ICIAR |
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Notes |
ADAS; 600.055 |
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Call Number |
Admin @ si @ ViS2013 |
Serial |
2562 |
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Author |
Carlo Gatta; Juan Diego Gomez; Francesco Ciompi; Oriol Rodriguez-Leor; Petia Radeva |
![goto web page (via DOI) doi](img/doi.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Toward robust myocardial blush grade estimation in contrast angiography |
Type |
Conference Article |
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Year |
2009 |
Publication |
4th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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5524 |
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Pages |
249–256 |
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Abstract |
The assessment of Myocardial Blush Grade after primary angioplasty is a precious diagnostic tool to understand if the patient needs further medication or the use of specifics drugs. Unfortunately, the assessment of MBG is difficult for non highly specialized staff. Experimental data show that there is poor correlation between MBG assessment of low and high specialized staff, thus reducing its applicability. This paper proposes a method able to achieve an objective measure of MBG, or a set of parameters that correlates with the MBG. The method tracks the blush area starting from just one single frame tagged by the physician. As a consequence, the blush area is kept isolated from contaminating phenomena such as diaphragm and arteries movements. We also present a method to extract four parameters that are expected to correlate with the MBG. Preliminary results show that the method is capable of extracting interesting information regarding the behavior of the myocardial perfusion. |
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Address ![sorted by Address field, descending order (down)](img/sort_desc.gif) |
Póvoa de Varzim, Portugal |
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Springer Berlin Heidelberg |
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Abbreviated Series Title |
LNCS |
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0302-9743 |
ISBN |
978-3-642-02171-8 |
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IbPRIA |
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Notes |
MILAB |
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no |
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Call Number |
BCNPCL @ bcnpcl @ GGC2009 |
Serial |
1161 |
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Permanent link to this record |
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Author |
Francesco Ciompi; Oriol Pujol; Oriol Rodriguez-Leor; Carlo Gatta; Angel Serrano; Petia Radeva |
![goto web page (via DOI) doi](img/doi.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Enhancing In-Vitro IVUS Data for Tissue Characterization |
Type |
Conference Article |
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Year |
2009 |
Publication |
4th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
5524 |
Issue |
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Pages |
241–248 |
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Abstract |
Intravascular Ultrasound (IVUS) data validation is usually performed by comparing post-mortem (in-vitro) IVUS data and corresponding histological analysis of the tissue, obtaining a reliable ground truth. The main drawback of this method is the few number of available study cases due to the complex procedure of histological analysis. In this work we propose a novel semi-supervised approach to enhance the in-vitro training set by including examples from in-vivo coronary plaques data set. For this purpose, a Sequential Floating Forward Selection method is applied on in-vivo data and plaque characterization performances are evaluated by Leave-One-Patient-Out cross-validation technique. Supervised data inclusion improves global classification accuracy from 89.39% to 91.82%. |
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Address ![sorted by Address field, descending order (down)](img/sort_desc.gif) |
Póvoa de Varzim, Portugal |
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Publisher |
Springer Berlin Heidelberg |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-02171-8 |
Medium |
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Area |
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Expedition |
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Conference |
IbPRIA |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ CPR2009a |
Serial |
1162 |
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Permanent link to this record |