| Records |
| Author |
Wenjuan Gong; Jordi Gonzalez; Xavier Roca |
| Title |
Human Action Recognition based on Estimated Weak Poses |
Type |
Journal Article |
| Year |
2012 |
Publication |
EURASIP Journal on Advances in Signal Processing |
Abbreviated Journal |
EURASIPJ |
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
We present a novel method for human action recognition (HAR) based on estimated poses from image sequences. We use 3D human pose data as additional information and propose a compact human pose representation, called a weak pose, in a low-dimensional space while still keeping the most discriminative information for a given pose. With predicted poses from image features, we map the problem from image feature space to pose space, where a Bag of Poses (BOP) model is learned for the final goal of HAR. The BOP model is a modified version of the classical bag of words pipeline by building the vocabulary based on the most representative weak poses for a given action. Compared with the standard k-means clustering, our vocabulary selection criteria is proven to be more efficient and robust against the inherent challenges of action recognition. Moreover, since for action recognition the ordering of the poses is discriminative, the BOP model incorporates temporal information: in essence, groups of consecutive poses are considered together when computing the vocabulary and assignment. We tested our method on two well-known datasets: HumanEva and IXMAS, to demonstrate that weak poses aid to improve action recognition accuracies. The proposed method is scene-independent and is comparable with the state-of-art method. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
Language  |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
ISE |
Approved |
no |
| Call Number |
Admin @ si @ GGR2012 |
Serial |
2003 |
| Permanent link to this record |
| |
|
| |
| Author |
Noha Elfiky; Jordi Gonzalez; Xavier Roca |
| Title |
Compact and Adaptive Spatial Pyramids for Scene Recognition |
Type |
Journal Article |
| Year |
2012 |
Publication |
Image and Vision Computing |
Abbreviated Journal |
IMAVIS |
| Volume |
30 |
Issue |
8 |
Pages |
492–500 |
| Keywords |
|
| Abstract |
Most successful approaches on scenerecognition tend to efficiently combine global image features with spatial local appearance and shape cues. On the other hand, less attention has been devoted for studying spatial texture features within scenes. Our method is based on the insight that scenes can be seen as a composition of micro-texture patterns. This paper analyzes the role of texture along with its spatial layout for scenerecognition. However, one main drawback of the resulting spatial representation is its huge dimensionality. Hence, we propose a technique that addresses this problem by presenting a compactSpatialPyramid (SP) representation. The basis of our compact representation, namely, CompactAdaptiveSpatialPyramid (CASP) consists of a two-stages compression strategy. This strategy is based on the Agglomerative Information Bottleneck (AIB) theory for (i) compressing the least informative SP features, and, (ii) automatically learning the most appropriate shape for each category. Our method exceeds the state-of-the-art results on several challenging scenerecognition data sets. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
ISE |
Approved |
no |
| Call Number |
Admin @ si @ EGR2012 |
Serial |
2004 |
| Permanent link to this record |
| |
|
| |
| Author |
Jordi Gonzalez; Thomas B. Moeslund; Liang Wang |
| Title |
Semantic Understanding of Human Behaviors in Image Sequences: From video-surveillance to video-hermeneutics |
Type |
Journal Article |
| Year |
2012 |
Publication |
Computer Vision and Image Understanding |
Abbreviated Journal |
CVIU |
| Volume |
116 |
Issue |
3 |
Pages |
305–306 |
| Keywords |
|
| Abstract |
Purpose: Atheromatic plaque progression is affected, among others phenomena, by biomechanical, biochemical, and physiological factors. In this paper, the authors introduce a novel framework able to provide both morphological (vessel radius, plaque thickness, and type) and biomechanical (wall shear stress and Von Mises stress) indices of coronary arteries.Methods: First, the approach reconstructs the three-dimensional morphology of the vessel from intravascular ultrasound (IVUS) and Angiographic sequences, requiring minimal user interaction. Then, a computational pipeline allows to automatically assess fluid-dynamic and mechanical indices. Ten coronary arteries are analyzed illustrating the capabilities of the tool and confirming previous technical and clinical observations.Results: The relations between the arterial indices obtained by IVUS measurement and simulations have been quantitatively analyzed along the whole surface of the artery, extending the analysis of the coronary arteries shown in previous state of the art studies. Additionally, for the first time in the literature, the framework allows the computation of the membrane stresses using a simplified mechanical model of the arterial wall.Conclusions: Circumferentially (within a given frame), statistical analysis shows an inverse relation between the wall shear stress and the plaque thickness. At the global level (comparing a frame within the entire vessel), it is observed that heavy plaque accumulations are in general calcified and are located in the areas of the vessel having high wall shear stress. Finally, in their experiments the inverse proportionality between fluid and structural stresses is observed. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
1077-3142 |
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
ISE |
Approved |
no |
| Call Number |
Admin @ si @ GMW2012 |
Serial |
2005 |
| Permanent link to this record |
| |
|
| |
| Author |
Antonio Hernandez; Nadezhda Zlateva; Alexander Marinov; Miguel Reyes; Petia Radeva; Dimo Dimov; Sergio Escalera |
| Title |
Human Limb Segmentation in Depth Maps based on Spatio-Temporal Graph Cuts Optimization |
Type |
Journal Article |
| Year |
2012 |
Publication |
Journal of Ambient Intelligence and Smart Environments |
Abbreviated Journal |
JAISE |
| Volume |
4 |
Issue |
6 |
Pages |
535-546 |
| Keywords |
Multi-modal vision processing; Random Forest; Graph-cuts; multi-label segmentation; human body segmentation |
| Abstract |
We present a framework for object segmentation using depth maps based on Random Forest and Graph-cuts theory, and apply it to the segmentation of human limbs. First, from a set of random depth features, Random Forest is used to infer a set of label probabilities for each data sample. This vector of probabilities is used as unary term in α−β swap Graph-cuts algorithm. Moreover, depth values of spatio-temporal neighboring data points are used as boundary potentials. Results on a new multi-label human depth data set show high performance in terms of segmentation overlapping of the novel methodology compared to classical approaches. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
1876-1364 |
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
Admin @ si @ HZM2012a |
Serial |
2006 |
| Permanent link to this record |
| |
|
| |
| Author |
Sophie Wuerger; Kaida Xiao; Dimitris Mylonas; Q. Huang; Dimosthenis Karatzas; Galina Paramei |
| Title |
Blue green color categorization in mandarin english speakers |
Type |
Journal Article |
| Year |
2012 |
Publication |
Journal of the Optical Society of America A |
Abbreviated Journal |
JOSA A |
| Volume |
29 |
Issue |
2 |
Pages |
A102-A1207 |
| Keywords |
|
| Abstract |
Observers are faster to detect a target among a set of distracters if the targets and distracters come from different color categories. This cross-boundary advantage seems to be limited to the right visual field, which is consistent with the dominance of the left hemisphere for language processing [Gilbert et al., Proc. Natl. Acad. Sci. USA 103, 489 (2006)]. Here we study whether a similar visual field advantage is found in the color identification task in speakers of Mandarin, a language that uses a logographic system. Forty late Mandarin-English bilinguals performed a blue-green color categorization task, in a blocked design, in their first language (L1: Mandarin) or second language (L2: English). Eleven color singletons ranging from blue to green were presented for 160 ms, randomly in the left visual field (LVF) or right visual field (RVF). Color boundary and reaction times (RTs) at the color boundary were estimated in L1 and L2, for both visual fields. We found that the color boundary did not differ between the languages; RTs at the color boundary, however, were on average more than 100 ms shorter in the English compared to the Mandarin sessions, but only when the stimuli were presented in the RVF. The finding may be explained by the script nature of the two languages: Mandarin logographic characters are analyzed visuospatially in the right hemisphere, which conceivably facilitates identification of color presented to the LVF. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ WXM2012 |
Serial |
2007 |
| Permanent link to this record |
| |
|
| |
| Author |
Yunchao Gong; Svetlana Lazebnik; Albert Gordo; Florent Perronnin |
| Title |
Iterative quantization: A procrustean approach to learning binary codes for Large-Scale Image Retrieval |
Type |
Journal Article |
| Year |
2012 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence |
Abbreviated Journal |
TPAMI |
| Volume |
35 |
Issue |
12 |
Pages |
2916-2929 |
| Keywords |
|
| Abstract |
This paper addresses the problem of learning similarity-preserving binary codes for efficient similarity search in large-scale image collections. We formulate this problem in terms of finding a rotation of zero-centered data so as to minimize the quantization error of mapping this data to the vertices of a zero-centered binary hypercube, and propose a simple and efficient alternating minimization algorithm to accomplish this task. This algorithm, dubbed iterative quantization (ITQ), has connections to multi-class spectral clustering and to the orthogonal Procrustes problem, and it can be used both with unsupervised data embeddings such as PCA and supervised embeddings such as canonical correlation analysis (CCA). The resulting binary codes significantly outperform several other state-of-the-art methods. We also show that further performance improvements can result from transforming the data with a nonlinear kernel mapping prior to PCA or CCA. Finally, we demonstrate an application of ITQ to learning binary attributes or “classemes” on the ImageNet dataset. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0162-8828 |
ISBN |
978-1-4577-0394-2 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ GLG 2012b |
Serial |
2008 |
| Permanent link to this record |
| |
|
| |
| Author |
Albert Clapes; Miguel Reyes; Sergio Escalera |
| Title |
User Identification and Object Recognition in Clutter Scenes Based on RGB-Depth Analysis |
Type |
Conference Article |
| Year |
2012 |
Publication |
7th Conference on Articulated Motion and Deformable Objects |
Abbreviated Journal |
|
| Volume |
7378 |
Issue |
|
Pages |
1-11 |
| Keywords |
|
| Abstract |
We propose an automatic system for user identification and object recognition based on multi-modal RGB-Depth data analysis. We model a RGBD environment learning a pixel-based background Gaussian distribution. Then, user and object candidate regions are detected and recognized online using robust statistical approaches over RGBD descriptions. Finally, the system saves the historic of user-object assignments, being specially useful for surveillance scenarios. The system has been evaluated on a novel data set containing different indoor/outdoor scenarios, objects, and users, showing accurate recognition and better performance than standard state-of-the-art approaches. |
| Address |
Mallorca |
| 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 |
978-3-642-31566-4 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
AMDO |
| Notes |
HUPBA;MILAB |
Approved |
no |
| Call Number |
Admin @ si @ CRE2012 |
Serial |
2010 |
| Permanent link to this record |
| |
|
| |
| Author |
Diego Cheda; Daniel Ponsa; Antonio Lopez |
| Title |
Monocular Egomotion Estimation based on Image Matching |
Type |
Conference Article |
| Year |
2012 |
Publication |
1st International Conference on Pattern Recognition Applications and Methods |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
425-430 |
| Keywords |
SLAM |
| Abstract |
|
| Address |
Portugal |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
ICPRAM |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ CPL2012a;; ADAS @ adas @ |
Serial |
2011 |
| Permanent link to this record |
| |
|
| |
| Author |
Diego Cheda; Daniel Ponsa; Antonio Lopez |
| Title |
Monocular Depth-based Background Estimation |
Type |
Conference Article |
| Year |
2012 |
Publication |
7th International Conference on Computer Vision Theory and Applications |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
323-328 |
| Keywords |
|
| Abstract |
In this paper, we address the problem of reconstructing the background of a scene from a video sequence with occluding objects. The images are taken by hand-held cameras. Our method composes the background by selecting the appropriate pixels from previously aligned input images. To do that, we minimize a cost function that penalizes the deviations from the following assumptions: background represents objects whose distance to the camera is maximal, and background objects are stationary. Distance information is roughly obtained by a supervised learning approach that allows us to distinguish between close and distant image regions. Moving foreground objects are filtered out by using stationariness and motion boundary constancy measurements. The cost function is minimized by a graph cuts method. We demonstrate the applicability of our approach to recover an occlusion-free background in a set of sequences. |
| Address |
Roma |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
VISAPP |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ CPL2012b; ADAS @ adas @ cpl2012e |
Serial |
2012 |
| Permanent link to this record |
| |
|
| |
| Author |
Diego Cheda; Daniel Ponsa; Antonio Lopez |
| Title |
Pedestrian Candidates Generation using Monocular Cues |
Type |
Conference Article |
| Year |
2012 |
Publication |
IEEE Intelligent Vehicles Symposium |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
7-12 |
| Keywords |
pedestrian detection |
| Abstract |
Common techniques for pedestrian candidates generation (e.g., sliding window approaches) are based on an exhaustive search over the image. This implies that the number of windows produced is huge, which translates into a significant time consumption in the classification stage. In this paper, we propose a method that significantly reduces the number of windows to be considered by a classifier. Our method is a monocular one that exploits geometric and depth information available on single images. Both representations of the world are fused together to generate pedestrian candidates based on an underlying model which is focused only on objects standing vertically on the ground plane and having certain height, according with their depths on the scene. We evaluate our algorithm on a challenging dataset and demonstrate its application for pedestrian detection, where a considerable reduction in the number of candidate windows is reached. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
IEEE Xplore |
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
1931-0587 |
ISBN |
978-1-4673-2119-8 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
IV |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ CPL2012c; ADAS @ adas @ cpl2012d |
Serial |
2013 |
| Permanent link to this record |
| |
|
| |
| Author |
Fernando Barrera; Felipe Lumbreras; Angel Sappa |
| Title |
Evaluation of Similarity Functions in Multimodal Stereo |
Type |
Conference Article |
| Year |
2012 |
Publication |
9th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
|
| Volume |
7324 |
Issue |
I |
Pages |
320-329 |
| Keywords |
Aveiro, Portugal |
| Abstract |
This paper presents an evaluation framework for multimodal stereo matching, which allows to compare the performance of four similarity functions. Additionally, it presents details of a multimodal stereo head that supply thermal infrared and color images, as well as, aspects of its calibration and rectification. The pipeline includes a novel method for the disparity selection, which is suitable for evaluating the similarity functions. Finally, a benchmark for comparing different initializations of the proposed framework is presented. Similarity functions are based on mutual information, gradient orientation and scale space representations. Their evaluation is performed using two metrics: i) disparity error, and ii) number of correct matches on planar regions. In addition to the proposed evaluation, the current paper also shows that 3D sparse representations can be recovered from such a multimodal stereo head. |
| 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 |
978-3-642-31294-6 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
ICIAR |
| Notes |
ADAS |
Approved |
no |
| Call Number |
BLS2012a |
Serial |
2014 |
| Permanent link to this record |
| |
|
| |
| Author |
Miguel Oliveira; Angel Sappa; V. Santos |
| Title |
Color Correction using 3D Gaussian Mixture Models |
Type |
Conference Article |
| Year |
2012 |
Publication |
9th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
|
| Volume |
7324 |
Issue |
I |
Pages |
97-106 |
| Keywords |
|
| Abstract |
The current paper proposes a novel color correction approach based on a probabilistic segmentation framework by using 3D Gaussian Mixture Models. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. The proposed approach is evaluated using both a recently published metric and two large data sets composed of seventy images. The evaluation is performed by comparing our algorithm with eight well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches. |
| 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 |
10.1007/978-3-642-31295-3_12 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
ICIAR |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ OSS2012a |
Serial |
2015 |
| Permanent link to this record |
| |
|
| |
| Author |
Fernando Barrera; Felipe Lumbreras; Cristhian Aguilera; Angel Sappa |
| Title |
Planar-Based Multispectral Stereo |
Type |
Conference Article |
| Year |
2012 |
Publication |
11th Quantitative InfraRed Thermography |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
|
| Address |
Naples, Italy |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
QIRT |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ BLA2012 |
Serial |
2016 |
| Permanent link to this record |
| |
|
| |
| Author |
Cristhian Aguilera; Fernando Barrera; Angel Sappa; Ricardo Toledo |
| Title |
A Novel SIFT-Like-Based Approach for FIR-VS Images Registration |
Type |
Conference Article |
| Year |
2012 |
Publication |
11th Quantitative InfraRed Thermography |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
|
| Address |
Naples, Italy |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
QIRT |
| Notes |
ADAS; TV |
Approved |
no |
| Call Number |
Admin @ si @ ABS2012 |
Serial |
2017 |
| Permanent link to this record |
| |
|
| |
| Author |
Monica Piñol; Angel Sappa; Angeles Lopez; Ricardo Toledo |
| Title |
Feature Selection Based on Reinforcement Learning for Object Recognition |
Type |
Conference Article |
| Year |
2012 |
Publication |
Adaptive Learning Agents Workshop |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
33-39 |
| Keywords |
|
| Abstract |
|
| Address |
Valencia |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
ALA |
| Notes |
ADAS; RV |
Approved |
no |
| Call Number |
Admin @ si @ PSL2012 |
Serial |
2018 |
| Permanent link to this record |
