| |
Records |
Links |
|
Author |
G. de Oliveira; Mariella Dimiccoli; Petia Radeva |
|
| |
Title |
Egocentric Image Retrieval With Deep Convolutional Neural Networks |
Type |
Conference Article |
| |
Year |
2016 |
Publication |
19th International Conference of the Catalan Association for Artificial Intelligence |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
71-76 |
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
Barcelona; Spain; October 2016 |
|
| |
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  |
CCIA |
|
| |
Notes |
MILAB |
Approved |
no |
|
| |
Call Number |
Admin @ si @ODR2016 |
Serial |
2790 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Jose A. Garcia; David Masip; Valerio Sbragaglia; Jacopo Aguzzi |
|
| |
Title |
Automated Identification and Tracking of Nephrops norvegicus (L.) Using Infrared and Monochromatic Blue Light |
Type |
Conference Article |
| |
Year |
2016 |
Publication |
19th International Conference of the Catalan Association for Artificial Intelligence |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
computer vision; video analysis; object recognition; tracking; behaviour; social; decapod; Nephrops norvegicus |
|
| |
Abstract |
Automated video and image analysis can be a very efficient tool to analyze
animal behavior based on sociality, especially in hard access environments
for researchers. The understanding of this social behavior can play a key role in the sustainable design of capture policies of many species. This paper proposes the use of computer vision algorithms to identify and track a specific specie, the Norway lobster, Nephrops norvegicus, a burrowing decapod with relevant commercial value which is captured by trawling. These animals can only be captured when are engaged in seabed excursions, which are strongly related with their social behavior.
This emergent behavior is modulated by the day-night cycle, but their social
interactions remain unknown to the scientific community. The paper introduces an identification scheme made of four distinguishable black and white tags (geometric shapes). The project has recorded 15-day experiments in laboratory pools, under monochromatic blue light (472 nm.) and darkness conditions (recorded using Infra Red light). Using this massive image set, we propose a comparative of state-ofthe-art computer vision algorithms to distinguish and track the different animals’ movements. We evaluate the robustness to the high noise presence in the infrared video signals and free out-of-plane rotations due to animal movement. The experiments show promising accuracies under a cross-validation protocol, being adaptable to the automation and analysis of large scale data. In a second contribution, we created an extensive dataset of shapes (46027 different shapes) from four daily experimental video recordings, which will be available to the community. |
|
| |
Address |
Barcelona; Spain; October 2016 |
|
| |
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 |
CCIA |
|
| |
Notes |
OR;MV; |
Approved |
no |
|
| |
Call Number |
Admin @ si @ GMS2016 |
Serial |
2816 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Petia Radeva |
|
| |
Title |
Can Deep Learning and Egocentric Vision for Visual Lifelogging Help Us Eat Better? |
Type |
Conference Article |
| |
Year |
2016 |
Publication |
19th International Conference of the Catalan Association for Artificial Intelligence |
Abbreviated Journal |
|
|
| |
Volume |
4 |
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
Barcelona; October 2016 |
|
| |
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 |
CCIA |
|
| |
Notes |
MILAB |
Approved |
no |
|
| |
Call Number |
Admin @ si @ Rad2016 |
Serial |
2832 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Vassileios Balntas; Edgar Riba; Daniel Ponsa; Krystian Mikolajczyk |
|
| |
Title |
Learning local feature descriptors with triplets and shallow convolutional neural networks |
Type |
Conference Article |
| |
Year |
2016 |
Publication |
27th British Machine Vision Conference |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
It has recently been demonstrated that local feature descriptors based on convolutional neural networks (CNN) can significantly improve the matching performance. Previous work on learning such descriptors has focused on exploiting pairs of positive and negative patches to learn discriminative CNN representations. In this work, we propose to utilize triplets of training samples, together with in-triplet mining of hard negatives.
We show that our method achieves state of the art results, without the computational overhead typically associated with mining of negatives and with lower complexity of the network architecture. We compare our approach to recently introduced convolutional local feature descriptors, and demonstrate the advantages of the proposed methods in terms of performance and speed. We also examine different loss functions associated with triplets. |
|
| |
Address |
York; UK; September 2016 |
|
| |
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 |
BMVC |
|
| |
Notes |
ADAS; 600.086 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ BRP2016 |
Serial |
2818 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Arash Akbarinia; C. Alejandro Parraga |
|
| |
Title |
Biologically plausible boundary detection |
Type |
Conference Article |
| |
Year |
2016 |
Publication |
27th British Machine Vision Conference |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
Edges are key components of any visual scene to the extent that we can recognise objects merely by their silhouettes. The human visual system captures edge information through neurons in the visual cortex that are sensitive to both intensity discontinuities and particular orientations. The “classical approach” assumes that these cells are only responsive to the stimulus present within their receptive fields, however, recent studies demonstrate that surrounding regions and inter-areal feedback connections influence their responses significantly. In this work we propose a biologically-inspired edge detection model in which orientation selective neurons are represented through the first derivative of a Gaussian function resembling double-opponent cells in the primary visual cortex (V1). In our model we account for four kinds of surround, i.e. full, far, iso- and orthogonal-orientation, whose contributions are contrast-dependant. The output signal from V1 is pooled in its perpendicular direction by larger V2 neurons employing a contrast-variant centre-surround kernel. We further introduce a feedback connection from higher-level visual areas to the lower ones. The results of our model on two benchmark datasets show a big improvement compared to the current non-learning and biologically-inspired state-of-the-art algorithms while being competitive to the learning-based methods. |
|
| |
Address |
York; UK; September 2016 |
|
| |
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 |
BMVC |
|
| |
Notes |
NEUROBIT; 600.068; 600.072 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ AkP2016a |
Serial |
2867 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Pejman Rasti; Tonis Uiboupin; Sergio Escalera; Gholamreza Anbarjafari |
|
| |
Title |
Convolutional Neural Network Super Resolution for Face Recognition in Surveillance Monitoring |
Type |
Conference Article |
| |
Year |
2016 |
Publication |
9th Conference on Articulated Motion and Deformable Objects |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
Palma de Mallorca; Spain; July 2016 |
|
| |
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 |
AMDO |
|
| |
Notes |
HuPBA;MILAB |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RUE2016 |
Serial |
2846 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Dennis H. Lundtoft; Kamal Nasrollahi; Thomas B. Moeslund; Sergio Escalera |
|
| |
Title |
Spatiotemporal Facial Super-Pixels for Pain Detection |
Type |
Conference Article |
| |
Year |
2016 |
Publication |
9th Conference on Articulated Motion and Deformable Objects |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
Facial images; Super-pixels; Spatiotemporal filters; Pain detection |
|
| |
Abstract |
Best student paper award.
Pain detection using facial images is of critical importance in many Health applications. Since pain is a spatiotemporal process, recent works on this topic employ facial spatiotemporal features to detect pain. These systems extract such features from the entire area of the face. In this paper, we show that by employing super-pixels we can divide the face into three regions, in a way that only one of these regions (about one third of the face) contributes to the pain estimation and the other two regions can be discarded. The experimental results on the UNBCMcMaster database show that the proposed system using this single region outperforms state-of-the-art systems in detecting no-pain scenarios, while it reaches comparable results in detecting weak and severe pain scenarios. |
|
| |
Address |
Palma de Mallorca; Spain; July 2016 |
|
| |
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 |
AMDO |
|
| |
Notes |
HUPBA;MILAB |
Approved |
no |
|
| |
Call Number |
Admin @ si @ LNM2016 |
Serial |
2847 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Mark Philip Philipsen; Anders Jorgensen; Thomas B. Moeslund; Sergio Escalera |
|
| |
Title |
RGB-D Segmentation of Poultry Entrails |
Type |
Conference Article |
| |
Year |
2016 |
Publication |
9th Conference on Articulated Motion and Deformable Objects |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
Best commercial paper award. |
|
| |
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 |
AMDO |
|
| |
Notes |
HuPBA;MILAB |
Approved |
no |
|
| |
Call Number |
Admin @ si @ PJM2016 |
Serial |
2848 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera |
|
| |
Title |
Action Recognition by Pairwise Proximity Function Support Vector Machines with Dynamic Time Warping Kernels |
Type |
Conference Article |
| |
Year |
2016 |
Publication |
29th Canadian Conference on Artificial Intelligence |
Abbreviated Journal |
|
|
| |
Volume |
9673 |
Issue |
|
Pages |
3-14 |
|
| |
Keywords |
|
|
| |
Abstract |
In the context of human action recognition using skeleton data, the 3D trajectories of joint points may be considered as multi-dimensional time series. The traditional recognition technique in the literature is based on time series dis(similarity) measures (such as Dynamic Time Warping). For these general dis(similarity) measures, k-nearest neighbor algorithms are a natural choice. However, k-NN classifiers are known to be sensitive to noise and outliers. In this paper, a new class of Support Vector Machine that is applicable to trajectory classification, such as action recognition, is developed by incorporating an efficient time-series distances measure into the kernel function. More specifically, the derivative of Dynamic Time Warping (DTW) distance measure is employed as the SVM kernel. In addition, the pairwise proximity learning strategy is utilized in order to make use of non-positive semi-definite (PSD) kernels in the SVM formulation. The recognition results of the proposed technique on two action recognition datasets demonstrates the ourperformance of our methodology compared to the state-of-the-art methods. Remarkably, we obtained 89 % accuracy on the well-known MSRAction3D dataset using only 3D trajectories of body joints obtained by Kinect |
|
| |
Address |
Victoria; Canada; May 2016 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer International Publishing |
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 |
AI |
|
| |
Notes |
HuPBA;MILAB; |
Approved |
no |
|
| |
Call Number |
Admin @ si @ BGE2016b |
Serial |
2770 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Gloria Fernandez Esparrach; Jorge Bernal; Cristina Rodriguez de Miguel; Debora Gil; Fernando Vilariño; Henry Cordova; Cristina Sanchez Montes; Isis Ara |
|
| |
Title |
Utilidad de la visión por computador para la localización de pólipos pequeños y planos |
Type |
Conference Article |
| |
Year |
2016 |
Publication |
XIX Reunión Nacional de la Asociación Española de Gastroenterología, Gastroenterology Hepatology |
Abbreviated Journal |
|
|
| |
Volume |
39 |
Issue |
2 |
Pages |
94 |
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
Madrid (Spain) |
|
| |
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 |
AEGASTRO |
|
| |
Notes |
MV; IAM; 600.097;SIAI |
Approved |
no |
|
| |
Call Number |
Admin @ si @FBR2016 |
Serial |
2779 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Marc Oliu; Ciprian Corneanu; Laszlo A. Jeni; Jeffrey F. Cohn; Takeo Kanade; Sergio Escalera |
|
| |
Title |
Continuous Supervised Descent Method for Facial Landmark Localisation |
Type |
Conference Article |
| |
Year |
2016 |
Publication |
13th Asian Conference on Computer Vision |
Abbreviated Journal |
|
|
| |
Volume |
10112 |
Issue |
|
Pages |
121-135 |
|
| |
Keywords |
|
|
| |
Abstract |
Recent methods for facial landmark location perform well on close-to-frontal faces but have problems in generalising to large head rotations. In order to address this issue we propose a second order linear regression method that is both compact and robust against strong rotations. We provide a closed form solution, making the method fast to train. We test the method’s performance on two challenging datasets. The first has been intensely used by the community. The second has been specially generated from a well known 3D face dataset. It is considerably more challenging, including a high diversity of rotations and more samples than any other existing public dataset. The proposed method is compared against state-of-the-art approaches, including RCPR, CGPRT, LBF, CFSS, and GSDM. Results upon both datasets show that the proposed method offers state-of-the-art performance on near frontal view data, improves state-of-the-art methods on more challenging head rotation problems and keeps a compact model size. |
|
| |
Address |
Taipei; Taiwan; November 2016 |
|
| |
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 |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ACCV |
|
| |
Notes |
HuPBA;MILAB; |
Approved |
no |
|
| |
Call Number |
Admin @ si @ OCJ2016 |
Serial |
2838 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
C. Butakoff; Simone Balocco; F.M. Sukno; C. Hoogendoorn; C. Tobon-Gomez; G. Avegliano; A.F. Frangi |
|
| |
Title |
Left-ventricular Epi- and Endocardium Extraction from 3D Ultrasound Images Using an Automatically Constructed 3D ASM |
Type |
Journal Article |
| |
Year |
2016 |
Publication |
Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization |
Abbreviated Journal |
CMBBE |
|
| |
Volume |
4 |
Issue |
5 |
Pages |
265-280 |
|
| |
Keywords |
ASM; cardiac segmentation; statistical model; shape model; 3D ultrasound; cardiac segmentation |
|
| |
Abstract |
In this paper, we propose an automatic method for constructing an active shape model (ASM) to segment the complete cardiac left ventricle in 3D ultrasound (3DUS) images, which avoids costly manual landmarking. The automatic construction of the ASM has already been addressed in the literature; however, the direct application of these methods to 3DUS is hampered by a high level of noise and artefacts. Therefore, we propose to construct the ASM by fusing the multidetector computed tomography data, to learn the shape, with the artificially generated 3DUS, in order to learn the neighbourhood of the boundaries. Our artificial images were generated by two approaches: a faster one that does not take into account the geometry of the transducer, and a more comprehensive one, implemented in Field II toolbox. The segmentation accuracy of our ASM was evaluated on 20 patients with left-ventricular asynchrony, demonstrating plausibility of the approach. |
|
| |
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 |
2168-1163 |
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
MILAB |
Approved |
no |
|
| |
Call Number |
Admin @ si @ BBS2016 |
Serial |
2449 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Svebor Karaman; Andrew Bagdanov; Lea Landucci; Gianpaolo D'Amico; Andrea Ferracani; Daniele Pezzatini; Alberto del Bimbo |
|
| |
Title |
Personalized multimedia content delivery on an interactive table by passive observation of museum visitors |
Type |
Journal Article |
| |
Year |
2016 |
Publication |
Multimedia Tools and Applications |
Abbreviated Journal |
MTAP |
|
| |
Volume |
75 |
Issue |
7 |
Pages |
3787-3811 |
|
| |
Keywords |
Computer vision; Video surveillance; Cultural heritage; Multimedia museum; Personalization; Natural interaction; Passive profiling |
|
| |
Abstract |
The amount of multimedia data collected in museum databases is growing fast, while the capacity of museums to display information to visitors is acutely limited by physical space. Museums must seek the perfect balance of information given on individual pieces in order to provide sufficient information to aid visitor understanding while maintaining sparse usage of the walls and guaranteeing high appreciation of the exhibit. Moreover, museums often target the interests of average visitors instead of the entire spectrum of different interests each individual visitor might have. Finally, visiting a museum should not be an experience contained in the physical space of the museum but a door opened onto a broader context of related artworks, authors, artistic trends, etc. In this paper we describe the MNEMOSYNE system that attempts to address these issues through a new multimedia museum experience. Based on passive observation, the system builds a profile of the artworks of interest for each visitor. These profiles of interest are then used to drive an interactive table that personalizes multimedia content delivery. The natural user interface on the interactive table uses the visitor’s profile, an ontology of museum content and a recommendation system to personalize exploration of multimedia content. At the end of their visit, the visitor can take home a personalized summary of their visit on a custom mobile application. In this article we describe in detail each component of our approach as well as the first field trials of our prototype system built and deployed at our permanent exhibition space at LeMurate (http://www.lemurate.comune.fi.it/lemurate/) in Florence together with the first results of the evaluation process during the official installation in the National Museum of Bargello (http://www.uffizi.firenze.it/musei/?m=bargello). |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer US |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
1380-7501 |
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
LAMP; 601.240; 600.079 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ KBL2016 |
Serial |
2520 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Miguel Angel Bautista; Antonio Hernandez; Sergio Escalera; Laura Igual; Oriol Pujol; Josep Moya; Veronica Violant; Maria Teresa Anguera |
|
| |
Title |
A Gesture Recognition System for Detecting Behavioral Patterns of ADHD |
Type |
Journal Article |
| |
Year |
2016 |
Publication |
IEEE Transactions on System, Man and Cybernetics, Part B |
Abbreviated Journal |
TSMCB |
|
| |
Volume |
46 |
Issue |
1 |
Pages |
136-147 |
|
| |
Keywords |
Gesture Recognition; ADHD; Gaussian Mixture Models; Convex Hulls; Dynamic Time Warping; Multi-modal RGB-Depth data |
|
| |
Abstract |
We present an application of gesture recognition using an extension of Dynamic Time Warping (DTW) to recognize behavioural patterns of Attention Deficit Hyperactivity Disorder (ADHD). We propose an extension of DTW using one-class classifiers in order to be able to encode the variability of a gesture category, and thus, perform an alignment between a gesture sample and a gesture class. We model the set of gesture samples of a certain gesture category using either GMMs or an approximation of Convex Hulls. Thus, we add a theoretical contribution to classical warping path in DTW by including local modeling of intra-class gesture variability. This methodology is applied in a clinical context, detecting a group of ADHD behavioural patterns defined by experts in psychology/psychiatry, to provide support to clinicians in the diagnose procedure. The proposed methodology is tested on a novel multi-modal dataset (RGB plus Depth) of ADHD children recordings with behavioural patterns. We obtain satisfying results when compared to standard state-of-the-art approaches in the DTW context. |
|
| |
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 |
HuPBA; MILAB; |
Approved |
no |
|
| |
Call Number |
Admin @ si @ BHE2016 |
Serial |
2566 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Mariella Dimiccoli |
|
| |
Title |
Figure-ground segregation: A fully nonlocal approach |
Type |
Journal Article |
| |
Year |
2016 |
Publication |
Vision Research |
Abbreviated Journal |
VR |
|
| |
Volume |
126 |
Issue |
|
Pages |
308-317 |
|
| |
Keywords |
Figure-ground segregation; Nonlocal approach; Directional linear voting; Nonlinear diffusion |
|
| |
Abstract |
We present a computational model that computes and integrates in a nonlocal fashion several configural cues for automatic figure-ground segregation. Our working hypothesis is that the figural status of each pixel is a nonlocal function of several geometric shape properties and it can be estimated without explicitly relying on object boundaries. The methodology is grounded on two elements: multi-directional linear voting and nonlinear diffusion. A first estimation of the figural status of each pixel is obtained as a result of a voting process, in which several differently oriented line-shaped neighborhoods vote to express their belief about the figural status of the pixel. A nonlinear diffusion process is then applied to enforce the coherence of figural status estimates among perceptually homogeneous regions. Computer simulations fit human perception and match the experimental evidence that several cues cooperate in defining figure-ground segregation. The results of this work suggest that figure-ground segregation involves feedback from cells with larger receptive fields in higher visual cortical areas. |
|
| |
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 |
MILAB; |
Approved |
no |
|
| |
Call Number |
Admin @ si @ Dim2016b |
Serial |
2623 |
|
| Permanent link to this record |
