| Records |
| Author |
Wenjuan Gong; Andrew Bagdanov; Xavier Roca; Jordi Gonzalez |
| Title |
Automatic Key Pose Selection for 3D Human Action Recognition |
Type |
Conference Article |
| Year |
2010 |
Publication |
6th International Conference on Articulated Motion and Deformable Objects |
Abbreviated Journal |
|
| Volume |
6169 |
Issue |
|
Pages |
290–299 |
| Keywords |
|
| Abstract |
This article describes a novel approach to the modeling of human actions in 3D. The method we propose is based on a “bag of poses” model that represents human actions as histograms of key-pose occurrences over the course of a video sequence. Actions are first represented as 3D poses using a sequence of 36 direction cosines corresponding to the angles 12 joints form with the world coordinate frame in an articulated human body model. These pose representations are then projected to three-dimensional, action-specific principal eigenspaces which we refer to as aSpaces. We introduce a method for key-pose selection based on a local-motion energy optimization criterion and we show that this method is more stable and more resistant to noisy data than other key-poses selection criteria for action recognition. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer Verlag |
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
ISSN  |
0302-9743 |
ISBN |
978-3-642-14060-0 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
AMDO |
| Notes |
ISE |
Approved |
no |
| Call Number |
DAG @ dag @ GBR2010 |
Serial |
1317 |
| Permanent link to this record |
| |
|
| |
| Author |
Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu |
| Title |
3D Texton Spaces for color-texture retrieval |
Type |
Conference Article |
| Year |
2010 |
Publication |
7th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
|
| Volume |
6111 |
Issue |
|
Pages |
354–363 |
| Keywords |
|
| Abstract |
Color and texture are visual cues of different nature, their integration in an useful visual descriptor is not an easy problem. One way to combine both features is to compute spatial texture descriptors independently on each color channel. Another way is to do the integration at the descriptor level. In this case the problem of normalizing both cues arises. In this paper we solve the latest problem by fusing color and texture through distances in texton spaces. Textons are the attributes of image blobs and they are responsible for texture discrimination as defined in Julesz’s Texton theory. We describe them in two low-dimensional and uniform spaces, namely, shape and color. The dissimilarity between color texture images is computed by combining the distances in these two spaces. Following this approach, we propose our TCD descriptor which outperforms current state of art methods in the two different approaches mentioned above, early combination with LBP and late combination with MPEG-7. This is done on an image retrieval experiment over a highly diverse texture dataset from Corel. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
A.C. Campilho and M.S. Kamel |
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-642-13771-6 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
ICIAR |
| Notes |
CIC |
Approved |
no |
| Call Number |
CAT @ cat @ ASV2010a |
Serial |
1325 |
| Permanent link to this record |
| |
|
| |
| Author |
Naveen Onkarappa; Angel Sappa |
| Title |
On-Board Monocular Vision System Pose Estimation through a Dense Optical Flow |
Type |
Conference Article |
| Year |
2010 |
Publication |
7th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
|
| Volume |
6111 |
Issue |
|
Pages |
230-239 |
| Keywords |
|
| Abstract |
This paper presents a robust technique for estimating on-board monocular vision system pose. The proposed approach is based on a dense optical flow that is robust against shadows, reflections and illumination changes. A RANSAC based scheme is used to cope with the outliers in the optical flow. The proposed technique is intended to be used in driver assistance systems for applications such as obstacle or pedestrian detection. Experimental results on different scenarios, both from synthetic and real sequences, shows usefulness of the proposed approach. |
| Address |
Povoa de Varzim (Portugal) |
| 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 |
978-3-642-13771-6 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
ICIAR |
| Notes |
ADAS |
Approved |
no |
| Call Number |
ADAS @ adas @ OnS2010 |
Serial |
1342 |
| Permanent link to this record |
| |
|
| |
| Author |
Jaume Gibert; Ernest Valveny |
| Title |
Graph Embedding based on Nodes Attributes Representatives and a Graph of Words Representation. |
Type |
Conference Article |
| Year |
2010 |
Publication |
13th International worshop on structural and syntactic pattern recognition and 8th international worshop on statistical pattern recognition |
Abbreviated Journal |
|
| Volume |
6218 |
Issue |
|
Pages |
223–232 |
| Keywords |
|
| Abstract |
Although graph embedding has recently been used to extend statistical pattern recognition techniques to the graph domain, some existing embeddings are usually computationally expensive as they rely on classical graph-based operations. In this paper we present a new way to embed graphs into vector spaces by first encapsulating the information stored in the original graph under another graph representation by clustering the attributes of the graphs to be processed. This new representation makes the association of graphs to vectors an easy step by just arranging both node attributes and the adjacency matrix in the form of vectors. To test our method, we use two different databases of graphs whose nodes attributes are of different nature. A comparison with a reference method permits to show that this new embedding is better in terms of classification rates, while being much more faster. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
In E.R. Hancock, R.C. Wilson, T. Windeatt, I. Ulusoy and F. Escolano, |
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-642-14979-5 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
S+SSPR |
| Notes |
DAG |
Approved |
no |
| Call Number |
DAG @ dag @ GiV2010 |
Serial |
1416 |
| Permanent link to this record |
| |
|
| |
| Author |
Marco Pedersoli; Jordi Gonzalez; Andrew Bagdanov; Juan J. Villanueva |
| Title |
Recursive Coarse-to-Fine Localization for fast Object Recognition |
Type |
Conference Article |
| Year |
2010 |
Publication |
11th European Conference on Computer Vision |
Abbreviated Journal |
|
| Volume |
6313 |
Issue |
II |
Pages |
280–293 |
| Keywords |
|
| Abstract |
Cascading techniques are commonly used to speed-up the scan of an image for object detection. However, cascades of detectors are slow to train due to the high number of detectors and corresponding thresholds to learn. Furthermore, they do not use any prior knowledge about the scene structure to decide where to focus the search. To handle these problems, we propose a new way to scan an image, where we couple a recursive coarse-to-fine refinement together with spatial constraints of the object location. For doing that we split an image into a set of uniformly distributed neighborhood regions, and for each of these we apply a local greedy search over feature resolutions. The neighborhood is defined as a scanning region that only one object can occupy. Therefore the best hypothesis is obtained as the location with maximum score and no thresholds are needed. We present an implementation of our method using a pyramid of HOG features and we evaluate it on two standard databases, VOC2007 and INRIA dataset. Results show that the Recursive Coarse-to-Fine Localization (RCFL) achieves a 12x speed-up compared to standard sliding windows. Compared with a cascade of multiple resolutions approach our method has slightly better performance in speed and Average-Precision. Furthermore, in contrast to cascading approach, the speed-up is independent of image conditions, the number of detected objects and clutter. |
| Address |
Crete (Greece) |
| 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 |
978-3-642-15566-6 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
ECCV |
| Notes |
ISE |
Approved |
no |
| Call Number |
DAG @ dag @ PGB2010 |
Serial |
1438 |
| Permanent link to this record |
| |
|
| |
| Author |
Carles Fernandez; Jordi Gonzalez; Xavier Roca |
| Title |
Automatic Learning of Background Semantics in Generic Surveilled Scenes |
Type |
Conference Article |
| Year |
2010 |
Publication |
11th European Conference on Computer Vision |
Abbreviated Journal |
|
| Volume |
6313 |
Issue |
II |
Pages |
678–692 |
| Keywords |
|
| Abstract |
Advanced surveillance systems for behavior recognition in outdoor traffic scenes depend strongly on the particular configuration of the scenario. Scene-independent trajectory analysis techniques statistically infer semantics in locations where motion occurs, and such inferences are typically limited to abnormality. Thus, it is interesting to design contributions that automatically categorize more specific semantic regions. State-of-the-art approaches for unsupervised scene labeling exploit trajectory data to segment areas like sources, sinks, or waiting zones. Our method, in addition, incorporates scene-independent knowledge to assign more meaningful labels like crosswalks, sidewalks, or parking spaces. First, a spatiotemporal scene model is obtained from trajectory analysis. Subsequently, a so-called GI-MRF inference process reinforces spatial coherence, and incorporates taxonomy-guided smoothness constraints. Our method achieves automatic and effective labeling of conceptual regions in urban scenarios, and is robust to tracking errors. Experimental validation on 5 surveillance databases has been conducted to assess the generality and accuracy of the segmentations. The resulting scene models are used for model-based behavior analysis. |
| Address |
Crete (Greece) |
| 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 |
978-3-642-15551-2 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
ECCV |
| Notes |
ISE |
Approved |
no |
| Call Number |
ISE @ ise @ FGR2010 |
Serial |
1439 |
| Permanent link to this record |
| |
|
| |
| Author |
Cesar Isaza; Joaquin Salas; Bogdan Raducanu |
| Title |
Toward the Detection of Urban Infrastructures Edge Shadows |
Type |
Conference Article |
| Year |
2010 |
Publication |
12th International Conference on Advanced Concepts for Intelligent Vision Systems |
Abbreviated Journal |
|
| Volume |
6474 |
Issue |
I |
Pages |
30–37 |
| Keywords |
|
| Abstract |
In this paper, we propose a novel technique to detect the shadows cast by urban infrastructure, such as buildings, billboards, and traffic signs, using a sequence of images taken from a fixed camera. In our approach, we compute two different background models in parallel: one for the edges and one for the reflected light intensity. An algorithm is proposed to train the system to distinguish between moving edges in general and edges that belong to static objects, creating an edge background model. Then, during operation, a background intensity model allow us to separate between moving and static objects. Those edges included in the moving objects and those that belong to the edge background model are subtracted from the current image edges. The remaining edges are the ones cast by urban infrastructure. Our method is tested on a typical crossroad scene and the results show that the approach is sound and promising. |
| Address |
Sydney, Australia |
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
eds. Blanc–Talon et al |
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-642-17687-6 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
ACIVS |
| Notes |
OR;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ ISR2010 |
Serial |
1458 |
| Permanent link to this record |
| |
|
| |
| Author |
Muhammad Muzzamil Luqman; Josep Llados; Jean-Yves Ramel; Thierry Brouard |
| Title |
A Fuzzy-Interval Based Approach For Explicit Graph Embedding, Recognizing Patterns in Signals, Speech, Images and Video |
Type |
Conference Article |
| Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
Abbreviated Journal |
|
| Volume |
6388 |
Issue |
|
Pages |
93–98 |
| Keywords |
|
| Abstract |
We present a new method for explicit graph embedding. Our algorithm extracts a feature vector for an undirected attributed graph. The proposed feature vector encodes details about the number of nodes, number of edges, node degrees, the attributes of nodes and the attributes of edges in the graph. The first two features are for the number of nodes and the number of edges. These are followed by w features for node degrees, m features for k node attributes and n features for l edge attributes — which represent the distribution of node degrees, node attribute values and edge attribute values, and are obtained by defining (in an unsupervised fashion), fuzzy-intervals over the list of node degrees, node attributes and edge attributes. Experimental results are provided for sample data of ICPR2010 contest GEPR. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer, 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 |
978-3-642-17710-1 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
ICPR |
| Notes |
DAG |
Approved |
no |
| Call Number |
DAG @ dag @ LLR2010 |
Serial |
1459 |
| Permanent link to this record |
| |
|
| |
| Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
| Title |
Graph of Words Embedding for Molecular Structure-Activity Relationship Analysis |
Type |
Conference Article |
| Year |
2010 |
Publication |
15th Iberoamerican Congress on Pattern Recognition |
Abbreviated Journal |
|
| Volume |
6419 |
Issue |
|
Pages |
30–37 |
| Keywords |
|
| Abstract |
Structure-Activity relationship analysis aims at discovering chemical activity of molecular compounds based on their structure. In this article we make use of a particular graph representation of molecules and propose a new graph embedding procedure to solve the problem of structure-activity relationship analysis. The embedding is essentially an arrangement of a molecule in the form of a vector by considering frequencies of appearing atoms and frequencies of covalent bonds between them. Results on two benchmark databases show the effectiveness of the proposed technique in terms of recognition accuracy while avoiding high operational costs in the transformation. |
| Address |
Sao Paulo, Brazil |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-642-16686-0 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
CIARP |
| Notes |
DAG |
Approved |
no |
| Call Number |
DAG @ dag @ GVB2010 |
Serial |
1462 |
| Permanent link to this record |
| |
|
| |
| Author |
Muhammad Anwer Rao; David Vazquez; Antonio Lopez |
| Title |
Color Contribution to Part-Based Person Detection in Different Types of Scenarios |
Type |
Conference Article |
| Year |
2011 |
Publication |
14th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
|
| Volume |
6855 |
Issue |
II |
Pages |
463-470 |
| Keywords |
Pedestrian Detection; Color |
| Abstract |
Camera-based person detection is of paramount interest due to its potential applications. The task is diffcult because the great variety of backgrounds (scenarios, illumination) in which persons are present, as well as their intra-class variability (pose, clothe, occlusion). In fact, the class person is one of the included in the popular PASCAL visual object classes (VOC) challenge. A breakthrough for this challenge, regarding person detection, is due to Felzenszwalb et al. These authors proposed a part-based detector that relies on histograms of oriented gradients (HOG) and latent support vector machines (LatSVM) to learn a model of the whole human body and its constitutive parts, as well as their relative position. Since the approach of Felzenszwalb et al. appeared new variants have been proposed, usually giving rise to more complex models. In this paper, we focus on an issue that has not attracted suficient interest up to now. In particular, we refer to the fact that HOG is usually computed from RGB color space, but other possibilities exist and deserve the corresponding investigation. In this paper we challenge RGB space with the opponent color space (OPP), which is inspired in the human vision system.We will compute the HOG on top of OPP, then we train and test the part-based human classifer by Felzenszwalb et al. using PASCAL VOC challenge protocols and person database. Our experiments demonstrate that OPP outperforms RGB. We also investigate possible differences among types of scenarios: indoor, urban and countryside. Interestingly, our experiments suggest that the beneficts of OPP with respect to RGB mainly come for indoor and countryside scenarios, those in which the human visual system was designed by evolution. |
| Address |
Seville, Spain |
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer |
Place of Publication |
Berlin Heidelberg |
Editor |
P. Real, D. Diaz, H. Molina, A. Berciano, W. Kropatsch |
| Language |
English |
Summary Language |
english |
Original Title |
Color Contribution to Part-Based Person Detection in Different Types of Scenarios |
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-642-23677-8 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
CAIP |
| Notes |
ADAS |
Approved |
no |
| Call Number |
ADAS @ adas @ RVL2011b |
Serial |
1665 |
| Permanent link to this record |
| |
|
| |
| Author |
Debora Gil; Aura Hernandez-Sabate; Mireia Burnat; Steven Jansen; Jordi Martinez-Vilalta |
| Title |
Structure-Preserving Smoothing of Biomedical Images |
Type |
Conference Article |
| Year |
2009 |
Publication |
13th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
|
| Volume |
5702 |
Issue |
|
Pages |
427-434 |
| Keywords |
non-linear smoothing; differential geometry; anatomical structures segmentation; cardiac magnetic resonance; computerized tomography. |
| Abstract |
Smoothing of biomedical images should preserve gray-level transitions between adjacent tissues, while restoring contours consistent with anatomical structures. Anisotropic diffusion operators are based on image appearance discontinuities (either local or contextual) and might fail at weak inter-tissue transitions. Meanwhile, the output of block-wise and morphological operations is prone to present a block structure due to the shape and size of the considered pixel neighborhood. In this contribution, we use differential geometry concepts to define a diffusion operator that restricts to image consistent level-sets. In this manner, the final state is a non-uniform intensity image presenting homogeneous inter-tissue transitions along anatomical structures, while smoothing intra-structure texture. Experiments on different types of medical images (magnetic resonance, computerized tomography) illustrate its benefit on a further process (such as segmentation) of images. |
| Address |
Münster, Germany |
| 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 |
978-3-642-03766-5 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
CAIP |
| Notes |
IAM |
Approved |
no |
| Call Number |
IAM @ iam @ GHB2009 |
Serial |
1527 |
| Permanent link to this record |
| |
|
| |
| Author |
Debora Gil; Petia Radeva |
| Title |
Curvature Vector Flow to Assure Convergent Deformable Models for Shape Modelling |
Type |
Book Chapter |
| Year |
2003 |
Publication |
Energy Minimization Methods In Computer Vision And Pattern Recognition |
Abbreviated Journal |
LNCS |
| Volume |
2683 |
Issue |
|
Pages |
357-372 |
| Keywords |
Initial condition; Convex shape; Non convex analysis; Increase; Segmentation; Gradient; Standard; Standards; Concave shape; Flow models; Tracking; Edge detection; Curvature |
| Abstract |
Poor convergence to concave shapes is a main limitation of snakes as a standard segmentation and shape modelling technique. The gradient of the external energy of the snake represents a force that pushes the snake into concave regions, as its internal energy increases when new inexion points are created. In spite of the improvement of the external energy by the gradient vector ow technique, highly non convex shapes can not be obtained, yet. In the present paper, we develop a new external energy based on the geometry of the curve to be modelled. By tracking back the deformation of a curve that evolves by minimum curvature ow, we construct a distance map that encapsulates the natural way of adapting to non convex shapes. The gradient of this map, which we call curvature vector ow (CVF), is capable of attracting a snake towards any contour, whatever its geometry. Our experiments show that, any initial snake condition converges to the curve to be modelled in optimal time. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer, Berlin |
Place of Publication |
Lisbon, PORTUGAL |
Editor |
Springer, B. |
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
Lecture Notes in Computer Science |
Abbreviated Series Title |
LNCS |
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
3-540-40498-8 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
IAM;MILAB |
Approved |
no |
| Call Number |
IAM @ iam @ GIR2003b |
Serial |
1535 |
| Permanent link to this record |
| |
|
| |
| Author |
Naveen Onkarappa; Angel Sappa |
| Title |
Space Variant Representations for Mobile Platform Vision Applications |
Type |
Conference Article |
| Year |
2011 |
Publication |
14th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
|
| Volume |
6855 |
Issue |
II |
Pages |
146-154 |
| Keywords |
|
| Abstract |
The log-polar space variant representation, motivated by biological vision, has been widely studied in the literature. Its data reduction and invariance properties made it useful in many vision applications. However, due to its nature, it fails in preserving features in the periphery. In the current work, as an attempt to overcome this problem, we propose a novel space-variant representation. It is evaluated and proved to be better than the log-polar representation in preserving the peripheral information, crucial for on-board mobile vision applications. The evaluation is performed by comparing log-polar and the proposed representation once they are used for estimating dense optical flow. |
| Address |
Seville, Spain |
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
P. Real, D. Diaz, H. Molina, A. Berciano, W. Kropatsch |
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-642-23677-8 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
CAIP |
| Notes |
ADAS |
Approved |
no |
| Call Number |
NaS2011; ADAS @ adas @ |
Serial |
1686 |
| Permanent link to this record |
| |
|
| |
| Author |
Mario Rojas; David Masip; Jordi Vitria |
| Title |
Automatic Detection of Facial Feature Points via HOGs and Geometric Prior Models |
Type |
Conference Article |
| Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
|
| Volume |
6669 |
Issue |
|
Pages |
371-378 |
| Keywords |
|
| Abstract |
Most applications dealing with problems involving the face require a robust estimation of the facial salient points. Nevertheless, this estimation is not usually an automated preprocessing step in applications dealing with facial expression recognition. In this paper we present a simple method to detect facial salient points in the face. It is based on a prior Point Distribution Model and a robust object descriptor. The model learns the distribution of the points from the training data, as well as the amount of variation in location each point exhibits. Using this model, we reduce the search areas to look for each point. In addition, we also exploit the global consistency of the points constellation, increasing the detection accuracy. The method was tested on two separate data sets and the results, in some cases, outperform the state of the art. |
| Address |
Las Palmas de Gran Canaria. Spain |
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-642-21256-7 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
IbPRIA |
| Notes |
OR;MV |
Approved |
no |
| Call Number |
Admin @ si @ RMV2011a |
Serial |
1731 |
| Permanent link to this record |
| |
|
| |
| Author |
Pierluigi Casale; Oriol Pujol; Petia Radeva |
| Title |
Human Activity Recognition from Accelerometer Data using a Wearable Device |
Type |
Conference Article |
| Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
|
| Volume |
6669 |
Issue |
|
Pages |
289-296 |
| Keywords |
|
| 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%. |
| Address |
Las Palmas de Gran Canaria. Spain |
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
Vitria, Jordi; Sanches, João Miguel Raposo; Hernández, Mario |
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-642-21256-7 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
IbPRIA |
| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
Admin @ si @ CPR2011a |
Serial |
1735 |
| Permanent link to this record |
