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Author |
Jaime Moreno; Xavier Otazu |
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Title |
Image compression algorithm based on Hilbert scanning of embedded quadTrees: an introduction of the Hi-SET coder |
Type |
Conference Article |
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Year |
2011 |
Publication |
IEEE International Conference on Multimedia and Expo |
Abbreviated Journal |
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Issue |
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Pages |
1-6 |
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Abstract |
In this work we present an effective and computationally simple algorithm for image compression based on Hilbert Scanning of Embedded quadTrees (Hi-SET). It allows to represent an image as an embedded bitstream along a fractal function. Embedding is an important feature of modern image compression algorithms, in this way Salomon in [1, pg. 614] cite that another feature and perhaps a unique one is the fact of achieving the best quality for the number of bits input by the decoder at any point during the decoding. Hi-SET possesses also this latter feature. Furthermore, the coder is based on a quadtree partition strategy, that applied to image transformation structures such as discrete cosine or wavelet transform allows to obtain an energy clustering both in frequency and space. The coding algorithm is composed of three general steps, using just a list of significant pixels. The implementation of the proposed coder is developed for gray-scale and color image compression. Hi-SET compressed images are, on average, 6.20dB better than the ones obtained by other compression techniques based on the Hilbert scanning. Moreover, Hi-SET improves the image quality in 1.39dB and 1.00dB in gray-scale and color compression, respectively, when compared with JPEG2000 coder. |
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ISSN |
1945-7871 |
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978-1-61284-348-3 |
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ICME |
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CIC |
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no |
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Call Number |
Admin @ si @ MoO2011a |
Serial |
2176 |
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Permanent link to this record |
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Author |
Jaime Moreno; Xavier Otazu |
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Title |
Image coder based on Hilbert scanning of embedded quadTrees |
Type |
Conference Article |
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Year |
2011 |
Publication |
Data Compression Conference |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
470-470 |
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Keywords |
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Abstract |
In this work we present an effective and computationally simple algorithm for image compression based on Hilbert Scanning of Embedded quadTrees (Hi-SET). It allows to represent an image as an embedded bitstream along a fractal function. Embedding is an important feature of modern image compression algorithms, in this way Salomon in [1, pg. 614] cite that another feature and perhaps a unique one is the fact of achieving the best quality for the number of bits input by the decoder at any point during the decoding. Hi-SET possesses also this latter feature. Furthermore, the coder is based on a quadtree partition strategy, that applied to image transformation structures such as discrete cosine or wavelet transform allows to obtain an energy clustering both in frequency and space. The coding algorithm is composed of three general steps, using just a list of significant pixels. |
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DCC |
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CIC |
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no |
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Call Number |
Admin @ si @ MoO2011b |
Serial |
2177 |
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Author |
Farhan Riaz; Fernando Vilariño; Mario Dinis-Ribeiro; Miguel Coimbraln |
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Title |
Identifying Potentially Cancerous Tissues in Chromoendoscopy Images |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
6669 |
Issue |
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Pages |
709-716 |
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Keywords |
Endoscopy, Computer Assisted Diagnosis, Gradient. |
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Abstract |
The dynamics of image acquisition conditions for gastroenterology imaging scenarios pose novel challenges for automatic computer assisted decision systems. Such systems should have the ability to mimic the tissue characterization of the physicians. In this paper, our objective is to compare some feature extraction methods to classify a Chromoendoscopy image into two different classes: Normal and Potentially cancerous. Results show that LoG filters generally give best classification accuracy among the other feature extraction methods considered. |
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Las Palmas de Gran Canaria. Spain |
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Publisher |
Springer |
Place of Publication |
Berlin |
Editor |
J. Vitria, J.M. Sanches, and M. Hernandez |
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LNCS |
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ISBN |
978-3-642-21256-7 |
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Area |
800 |
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Conference |
IbPRIA |
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Notes |
MV;SIAI |
Approved |
no |
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Call Number |
Admin @ si @ RVD2011; IAM @ iam @ RVD2011 |
Serial |
1726 |
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Permanent link to this record |
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Author |
Dimosthenis Karatzas; Sergi Robles; Joan Mas; Farshad Nourbakhsh; Partha Pratim Roy |
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Title |
ICDAR 2011 Robust Reading Competition – Challege 1: Reading Text in Born-Digital Images (Web and Email) |
Type |
Conference Article |
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Year |
2011 |
Publication |
11th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
1485-1490 |
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Abstract |
This paper presents the results of the first Challenge of ICDAR 2011 Robust Reading Competition. Challenge 1 is focused on the extraction of text from born-digital images, specifically from images found in Web pages and emails. The challenge was organized in terms of three tasks that look at different stages of the process: text localization, text segmentation and word recognition. In this paper we present the results of the challenge for all three tasks, and make an open call for continuous participation outside the context of ICDAR 2011. |
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Beijing, China |
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ISSN |
1520-5363 |
ISBN |
978-1-4577-1350-7 |
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Conference |
ICDAR |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ KRM2011 |
Serial |
1793 |
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Permanent link to this record |
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Author |
Victor Ponce; Mario Gorga; Xavier Baro; Sergio Escalera |
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Title |
Human Behavior Analysis from Video Data Using Bag-of-Gestures |
Type |
Conference Article |
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Year |
2011 |
Publication |
22nd International Joint Conference on Artificial Intelligence |
Abbreviated Journal |
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Volume |
3 |
Issue |
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Pages |
2836-2837 |
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Keywords |
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Abstract |
Human Behavior Analysis in Uncontrolled Environments can be categorized in two main challenges: 1) Feature extraction and 2) Behavior analysis from a set of corporal language vocabulary. In this work, we present our achievements characterizing some simple behaviors from visual data on different real applications and discuss our plan for future work: low level vocabulary definition from bag-of-gesture units and high level modelling and inference of human behaviors. |
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Address |
Barcelona |
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ISBN |
978-1-57735-516-8 |
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IJCAI |
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Notes |
HuPBA;MV |
Approved |
no |
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Call Number |
Admin @ si @ PGB2011b |
Serial |
1770 |
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Permanent link to this record |
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Author |
Pierluigi Casale; Oriol Pujol; Petia Radeva |
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Title |
Human Activity Recognition from Accelerometer Data using a Wearable Device |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
6669 |
Issue |
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Pages |
289-296 |
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Abstract |
Activity Recognition is an emerging field of research, born from the larger fields of ubiquitous computing, context-aware computing and multimedia. Recently, recognizing everyday life activities becomes one of the challenges for pervasive computing. In our work, we developed a novel wearable system easy to use and comfortable to bring. Our wearable system is based on a new set of 20 computationally efficient features and the Random Forest classifier. We obtain very encouraging results with classification accuracy of human activities recognition of up to 94%. |
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Address |
Las Palmas de Gran Canaria. Spain |
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Publisher |
Springer Berlin Heidelberg |
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Editor |
Vitria, Jordi; Sanches, João Miguel Raposo; Hernández, Mario |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-21256-7 |
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Conference |
IbPRIA |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ CPR2011a |
Serial |
1735 |
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Permanent link to this record |
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Author |
Maria del Camp Davesa |
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Title |
Human action categorization in image sequences |
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Report |
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Year |
2011 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
169 |
Issue |
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Pages |
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Address |
Bellaterra (Spain) |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Notes |
CiC;CIC |
Approved |
no |
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Call Number |
Admin @ si @ Dav2011 |
Serial |
1934 |
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Permanent link to this record |
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Author |
Gemma Roig; Xavier Boix; F. de la Torre; Joan Serrat; C. Vilella |
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Title |
Hierarchical CRF with product label spaces for parts-based Models |
Type |
Conference Article |
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Year |
2011 |
Publication |
IEEE Conference on Automatic Face and Gesture Recognition |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
657-664 |
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Keywords |
Shape; Computational modeling; Principal component analysis; Random variables; Color; Upper bound; Facial features |
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Abstract |
Non-rigid object detection is a challenging an open research problem in computer vision. It is a critical part in many applications such as image search, surveillance, human-computer interaction or image auto-annotation. Most successful approaches to non-rigid object detection make use of part-based models. In particular, Conditional Random Fields (CRF) have been successfully embedded into a discriminative parts-based model framework due to its effectiveness for learning and inference (usually based on a tree structure). However, CRF-based approaches do not incorporate global constraints and only model pairwise interactions. This is especially important when modeling object classes that may have complex parts interactions (e.g. facial features or body articulations), because neglecting them yields an oversimplified model with suboptimal performance. To overcome this limitation, this paper proposes a novel hierarchical CRF (HCRF). The main contribution is to build a hierarchy of part combinations by extending the label set to a hierarchy of product label spaces. In order to keep the inference computation tractable, we propose an effective method to reduce the new label set. We test our method on two applications: facial feature detection on the Multi-PIE database and human pose estimation on the Buffy dataset. |
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Address |
Santa Barbara, CA, USA, 2011 |
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Conference |
FG |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ RBT2011 |
Serial |
1862 |
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Permanent link to this record |
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Author |
David Fernandez; Josep Llados; Alicia Fornes |
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Title |
Handwritten Word Spotting in Old Manuscript Images Using a Pseudo-Structural Descriptor Organized in a Hash Structure |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
6669 |
Issue |
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Pages |
628-635 |
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Abstract |
There are lots of historical handwritten documents with information that can be used for several studies and projects. The Document Image Analysis and Recognition community is interested in preserving these documents and extracting all the valuable information from them. Handwritten word-spotting is the pattern classification task which consists in detecting handwriting word images. In this work, we have used a query-by-example formalism: we have matched an input image with one or multiple images from handwritten documents to determine the distance that might indicate a correspondence. We have developed an approach based in characteristic Loci Features stored in a hash structure. Document images of the marriage licences of the Cathedral of Barcelona are used as the benchmarking database. |
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Address |
Las Palmas de Gran Canaria. Spain |
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Corporate Author |
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Publisher |
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Place of Publication |
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Editor |
Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
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ISBN |
978-3-642-21256-7 |
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Conference |
IbPRIA |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ FLF2011 |
Serial |
1742 |
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Permanent link to this record |
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Author |
Miguel Reyes; Gabriel Dominguez; Sergio Escalera |
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Title |
Feature Weighting in Dynamic Time Warping for Gesture Recognition in Depth Data |
Type |
Conference Article |
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Year |
2011 |
Publication |
1st IEEE Workshop on Consumer Depth Cameras for Computer Vision |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
1182-1188 |
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Abstract |
We present a gesture recognition approach for depth video data based on a novel Feature Weighting approach within the Dynamic Time Warping framework. Depth features from human joints are compared through video sequences using Dynamic Time Warping, and weights are assigned to features based on inter-intra class gesture variability. Feature Weighting in Dynamic Time Warping is then applied for recognizing begin-end of gestures in data sequences. The obtained results recognizing several gestures in depth data show high performance compared with classical Dynamic Time Warping approach. |
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ISBN |
978-1-4673-0062-9 |
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Conference |
CDC4CV |
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Notes |
HuPBA;MILAB |
Approved |
no |
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Call Number |
Admin @ si @ RDE2011 |
Serial |
1893 |
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Permanent link to this record |
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Author |
Jordi Gonzalez; Josep M. Gonfaus; Carles Fernandez; Xavier Roca |
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Title |
Exploiting Natural-Language Interaction in Video Surveillance Systems |
Type |
Conference Article |
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Year |
2011 |
Publication |
V&L Net Workshop on Vision and Language |
Abbreviated Journal |
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Address |
Brighton, UK |
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VL |
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ISE |
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no |
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Call Number |
Admin @ si @ GGF2011 |
Serial |
1813 |
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Permanent link to this record |
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Author |
Alejandro Gonzalez Alzate |
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Title |
Evaluation of spatiotemporal descriptors for pedestrian detection in video sequences |
Type |
Report |
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Year |
2011 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
166 |
Issue |
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Pages |
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Address |
Bellaterra (Spain) |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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ADAS |
Approved |
no |
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Call Number |
Admin @ si @ Gon2011 |
Serial |
1932 |
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Permanent link to this record |
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Author |
Gerard Lacey; Fernando Vilariño |
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Title |
Endoscopy system with motion sensors |
Type |
Patent |
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Year |
2011 |
Publication |
US 2011/0032347 A1 |
Abbreviated Journal |
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An endoscopy system (1) comprises an endoscope (2) with a camera (3) at its tip. The endoscope extends through an endoscope guide (4) for guiding movement of the endoscope and for measurement of its movement as it enters the body. The guide (4) comprises a generally conical body (5) having a through passage (105) through which the endoscope (2) extends. A motion sensor comprises an optical transmitter (7) and a detector (8) mounted alongside the passage (105) to measure the insertion-withdrawal linear motion and also rotation of the endoscope by the endoscopist's hand. The system (1) also comprises a flexure controller (10) having wheels operated by the endoscopist. The camera (3), the motion sensor (7/8), and the flexure controller (10) are all connected to a processor (11) which feeds a display. |
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Address |
Jacobson Holman PPLC; 400 Seventh Street, N.W. Suite 600; Whashington DC 20004 DC |
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USPTO |
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Area |
800 |
Expedition |
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Notes |
MV;SIAI |
Approved |
no |
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Call Number |
IAM @ iam @ LaV2011 |
Serial |
1703 |
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Permanent link to this record |
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Author |
Koen E.A. van de Sande; Theo Gevers; Cees G.M. Snoek |
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Title |
Empowering Visual Categorization with the GPU |
Type |
Journal Article |
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Year |
2011 |
Publication |
IEEE Transactions on Multimedia |
Abbreviated Journal |
TMM |
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Volume |
13 |
Issue |
1 |
Pages |
60-70 |
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Keywords |
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Visual categorization is important to manage large collections of digital images and video, where textual meta-data is often incomplete or simply unavailable. The bag-of-words model has become the most powerful method for visual categorization of images and video. Despite its high accuracy, a severe drawback of this model is its high computational cost. As the trend to increase computational power in newer CPU and GPU architectures is to increase their level of parallelism, exploiting this parallelism becomes an important direction to handle the computational cost of the bag-of-words approach. When optimizing a system based on the bag-of-words approach, the goal is to minimize the time it takes to process batches of images. Additionally, we also consider power usage as an evaluation metric. In this paper, we analyze the bag-of-words model for visual categorization in terms of computational cost and identify two major bottlenecks: the quantization step and the classification step. We address these two bottlenecks by proposing two efficient algorithms for quantization and classification by exploiting the GPU hardware and the CUDA parallel programming model. The algorithms are designed to (1) keep categorization accuracy intact, (2) decompose the problem and (3) give the same numerical results. In the experiments on large scale datasets it is shown that, by using a parallel implementation on the Geforce GTX260 GPU, classifying unseen images is 4.8 times faster than a quad-core CPU version on the Core i7 920, while giving the exact same numerical results. In addition, we show how the algorithms can be generalized to other applications, such as text retrieval and video retrieval. Moreover, when the obtained speedup is used to process extra video frames in a video retrieval benchmark, the accuracy of visual categorization is improved by 29%. |
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Admin @ si @ SGS2011b |
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Author |
A. Toet; M. Henselmans; M.P. Lucassen; Theo Gevers |
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Emotional effects of dynamic textures |
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2011 |
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i-Perception |
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iPER |
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2 |
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9 |
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969 – 991 |
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This study explores the effects of various spatiotemporal dynamic texture characteristics on human emotions. The emotional experience of auditory (eg, music) and haptic repetitive patterns has been studied extensively. In contrast, the emotional experience of visual dynamic textures is still largely unknown, despite their natural ubiquity and increasing use in digital media. Participants watched a set of dynamic textures, representing either water or various different media, and self-reported their emotional experience. Motion complexity was found to have mildly relaxing and nondominant effects. In contrast, motion change complexity was found to be arousing and dominant. The speed of dynamics had arousing, dominant, and unpleasant effects. The amplitude of dynamics was also regarded as unpleasant. The regularity of the dynamics over the textures’ area was found to be uninteresting, nondominant, mildly relaxing, and mildly pleasant. The spatial scale of the dynamics had an unpleasant, arousing, and dominant effect, which was larger for textures with diverse content than for water textures. For water textures, the effects of spatial contrast were arousing, dominant, interesting, and mildly unpleasant. None of these effects were observed for textures of diverse content. The current findings are relevant for the design and synthesis of affective multimedia content and for affective scene indexing and retrieval. |
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2041-6695 |
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Admin @ si @THL2011 |
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1843 |
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