|
Records |
Links |
|
Author |
Oualid M. Benkarim; Petia Radeva; Laura Igual |
|
|
Title |
Label Consistent Multiclass Discriminative Dictionary Learning for MRI Segmentation |
Type |
Conference Article |
|
Year |
2014 |
Publication |
8th Conference on Articulated Motion and Deformable Objects |
Abbreviated Journal |
|
|
|
Volume |
8563 |
Issue |
|
Pages |
138-147 |
|
|
Keywords |
MRI segmentation; sparse representation; discriminative dic- tionary learning; multiclass classication |
|
|
Abstract |
The automatic segmentation of multiple subcortical structures in brain Magnetic Resonance Images (MRI) still remains a challenging task. In this paper, we address this problem using sparse representation and discriminative dictionary learning, which have shown promising results in compression, image denoising and recently in MRI segmentation. Particularly, we use multiclass dictionaries learned from a set of brain atlases to simultaneously segment multiple subcortical structures.
We also impose dictionary atoms to be specialized in one given class using label consistent K-SVD, which can alleviate the bias produced by unbalanced libraries, present when dealing with small structures. The proposed method is compared with other state of the art approaches for the segmentation of the Basal Ganglia of 35 subjects of a public dataset.
The promising results of the segmentation method show the eciency of the multiclass discriminative dictionary learning algorithms in MRI segmentation problems. |
|
|
Address |
Palma de Mallorca; July 2014 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer International Publishing |
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 |
978-3-319-08848-8 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
AMDO |
|
|
Notes |
MILAB; OR |
Approved |
no |
|
|
Call Number |
Admin @ si @ BRI2014 |
Serial |
2494 |
|
Permanent link to this record |
|
|
|
|
Author |
Marc Bolaños; Maite Garolera; Petia Radeva |
|
|
Title |
Video Segmentation of Life-Logging Videos |
Type |
Conference Article |
|
Year |
2014 |
Publication |
8th Conference on Articulated Motion and Deformable Objects |
Abbreviated Journal |
|
|
|
Volume |
8563 |
Issue |
|
Pages |
1-9 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
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 |
MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ BGR2014 |
Serial |
2558 |
|
Permanent link to this record |
|
|
|
|
Author |
Juan Ramon Terven Salinas; Joaquin Salas; Bogdan Raducanu |
|
|
Title |
Robust Head Gestures Recognition for Assistive Technology |
Type |
Book Chapter |
|
Year |
2014 |
Publication |
Pattern Recognition |
Abbreviated Journal |
|
|
|
Volume |
8495 |
Issue |
|
Pages |
152-161 |
|
|
Keywords |
|
|
|
Abstract |
This paper presents a system capable of recognizing six head gestures: nodding, shaking, turning right, turning left, looking up, and looking down. The main difference of our system compared to other methods is that the Hidden Markov Models presented in this paper, are fully connected and consider all possible states in any given order, providing the following advantages to the system: (1) allows unconstrained movement of the head and (2) it can be easily integrated into a wearable device (e.g. glasses, neck-hung devices), in which case it can robustly recognize gestures in the presence of ego-motion. Experimental results show that this approach outperforms common methods that use restricted HMMs for each gesture. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer International Publishing |
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 |
978-3-319-07490-0 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
OR;MV |
Approved |
no |
|
|
Call Number |
Admin @ si @ TSR2014b |
Serial |
2505 |
|
Permanent link to this record |
|
|
|
|
Author |
Carles Sanchez; Jorge Bernal; Debora Gil; F. Javier Sanchez |
|
|
Title |
On-line lumen centre detection in gastrointestinal and respiratory endoscopy |
Type |
Conference Article |
|
Year |
2013 |
Publication |
Second International Workshop Clinical Image-Based Procedures |
Abbreviated Journal |
|
|
|
Volume |
8361 |
Issue |
|
Pages |
31-38 |
|
|
Keywords |
Lumen centre detection; Bronchoscopy; Colonoscopy |
|
|
Abstract |
We present in this paper a novel lumen centre detection for gastrointestinal and respiratory endoscopic images. The proposed method is based on the appearance and geometry of the lumen, which we defined as the darkest image region which centre is a hub of image gradients. Experimental results validated on the first public annotated gastro-respiratory database prove the reliability of the method for a wide range of images (with precision over 95 %). |
|
|
Address |
Nagoya; Japan; September 2013 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer International Publishing |
Place of Publication |
|
Editor |
Erdt, Marius and Linguraru, Marius George and Oyarzun Laura, Cristina and Shekhar, Raj and Wesarg, Stefan and González Ballester, Miguel Angel and Drechsler, Klaus |
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-3-319-05665-4 |
Medium |
|
|
|
Area |
800 |
Expedition |
|
Conference |
CLIP |
|
|
Notes |
MV; IAM; 600.047; 600.044; 600.060 |
Approved |
no |
|
|
Call Number |
Admin @ si @ SBG2013 |
Serial |
2302 |
|
Permanent link to this record |
|
|
|
|
Author |
Alex Pardo; Albert Clapes; Sergio Escalera; Oriol Pujol |
|
|
Title |
Actions in Context: System for people with Dementia |
Type |
Conference Article |
|
Year |
2013 |
Publication |
2nd International Workshop on Citizen Sensor Networks (Citisen2013) at the European Conference on Complex Systems |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
3-14 |
|
|
Keywords |
Multi-modal data Fusion; Computer vision; Wearable sensors; Gesture recognition; Dementia |
|
|
Abstract |
In the next forty years, the number of people living with dementia is expected to triple. In the last stages, people affected by this disease become dependent. This hinders the autonomy of the patient and has a huge social impact in time, money and effort. Given this scenario, we propose an ubiquitous system capable of recognizing daily specific actions. The system fuses and synchronizes data obtained from two complementary modalities – ambient and egocentric. The ambient approach consists in a fixed RGB-Depth camera for user and object recognition and user-object interaction, whereas the egocentric point of view is given by a personal area network (PAN) formed by a few wearable sensors and a smartphone, used for gesture recognition. The system processes multi-modal data in real-time, performing paralleled task recognition and modality synchronization, showing high performance recognizing subjects, objects, and interactions, showing its reliability to be applied in real case scenarios. |
|
|
Address |
Barcelona; September 2013 |
|
|
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 |
0302-9743 |
ISBN |
978-3-319-04177-3 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ECCS |
|
|
Notes |
HUPBA;MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ PCE2013 |
Serial |
2354 |
|
Permanent link to this record |
|
|
|
|
Author |
Fadi Dornaika; Alireza Bosaghzadeh; Bogdan Raducanu |
|
|
Title |
Efficient Graph Construction for Label Propagation based Multi-observation Face Recognition |
Type |
Conference Article |
|
Year |
2013 |
Publication |
Human Behavior Understanding 4th International Workshop |
Abbreviated Journal |
|
|
|
Volume |
8212 |
Issue |
|
Pages |
124-135 |
|
|
Keywords |
|
|
|
Abstract |
Workshop on Human Behavior Understanding
Human-machine interaction is a hot topic nowadays in the communities of multimedia and computer vision. In this context, face recognition algorithms (used as primary cue for a person’s identity assessment) work well under controlled conditions but degrade significantly when tested in real-world environments. Recently, graph-based label propagation for multi-observation face recognition was proposed. However, the associated graphs were constructed in an ad-hoc manner (e.g., using the KNN graph) that cannot adapt optimally to the data. In this paper, we propose a novel approach for efficient and adaptive graph construction that can be used for multi-observation face recognition as well as for other recognition problems. Experimental results performed on Honda video face database, show a distinct advantage of the proposed method over the standard graph construction methods. |
|
|
Address |
Barcelona |
|
|
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 |
0302-9743 |
ISBN |
978-3-319-02713-5 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
HBU |
|
|
Notes |
OR;MV |
Approved |
no |
|
|
Call Number |
Admin @ si @ DBR2013 |
Serial |
2315 |
|
Permanent link to this record |
|
|
|
|
Author |
Arnau Baro; Pau Riba; Alicia Fornes |
|
|
Title |
Musigraph: Optical Music Recognition Through Object Detection and Graph Neural Network |
Type |
Conference Article |
|
Year |
2022 |
Publication |
Frontiers in Handwriting Recognition. International Conference on Frontiers in Handwriting Recognition (ICFHR2022) |
Abbreviated Journal |
|
|
|
Volume |
13639 |
Issue |
|
Pages |
171-184 |
|
|
Keywords |
Object detection; Optical music recognition; Graph neural network |
|
|
Abstract |
During the last decades, the performance of optical music recognition has been increasingly improving. However, and despite the 2-dimensional nature of music notation (e.g. notes have rhythm and pitch), most works treat musical scores as a sequence of symbols in one dimension, which make their recognition still a challenge. Thus, in this work we explore the use of graph neural networks for musical score recognition. First, because graphs are suited for n-dimensional representations, and second, because the combination of graphs with deep learning has shown a great performance in similar applications. Our methodology consists of: First, we will detect each isolated/atomic symbols (those that can not be decomposed in more graphical primitives) and the primitives that form a musical symbol. Then, we will build the graph taking as root node the notehead and as leaves those primitives or symbols that modify the note’s rhythm (stem, beam, flag) or pitch (flat, sharp, natural). Finally, the graph is translated into a human-readable character sequence for a final transcription and evaluation. Our method has been tested on more than five thousand measures, showing promising results. |
|
|
Address |
December 04 – 07, 2022; Hyderabad, India |
|
|
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 |
ICFHR |
|
|
Notes |
DAG; 600.162; 600.140; 602.230 |
Approved |
no |
|
|
Call Number |
Admin @ si @ BRF2022b |
Serial |
3740 |
|
Permanent link to this record |
|
|
|
|
Author |
Giuseppe De Gregorio; Sanket Biswas; Mohamed Ali Souibgui; Asma Bensalah; Josep Llados; Alicia Fornes; Angelo Marcelli |
|
|
Title |
A Few Shot Multi-representation Approach for N-Gram Spotting in Historical Manuscripts |
Type |
Conference Article |
|
Year |
2022 |
Publication |
Frontiers in Handwriting Recognition. International Conference on Frontiers in Handwriting Recognition (ICFHR2022) |
Abbreviated Journal |
|
|
|
Volume |
13639 |
Issue |
|
Pages |
3-12 |
|
|
Keywords |
N-gram spotting; Few-shot learning; Multimodal understanding; Historical handwritten collections |
|
|
Abstract |
Despite recent advances in automatic text recognition, the performance remains moderate when it comes to historical manuscripts. This is mainly because of the scarcity of available labelled data to train the data-hungry Handwritten Text Recognition (HTR) models. The Keyword Spotting System (KWS) provides a valid alternative to HTR due to the reduction in error rate, but it is usually limited to a closed reference vocabulary. In this paper, we propose a few-shot learning paradigm for spotting sequences of a few characters (N-gram) that requires a small amount of labelled training data. We exhibit that recognition of important n-grams could reduce the system’s dependency on vocabulary. In this case, an out-of-vocabulary (OOV) word in an input handwritten line image could be a sequence of n-grams that belong to the lexicon. An extensive experimental evaluation of our proposed multi-representation approach was carried out on a subset of Bentham’s historical manuscript collections to obtain some really promising results in this direction. |
|
|
Address |
December 04 – 07, 2022; Hyderabad, India |
|
|
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 |
ICFHR |
|
|
Notes |
DAG; 600.121; 600.162; 602.230; 600.140 |
Approved |
no |
|
|
Call Number |
Admin @ si @ GBS2022 |
Serial |
3733 |
|
Permanent link to this record |
|
|
|
|
Author |
Utkarsh Porwal; Alicia Fornes; Faisal Shafait (eds) |
|
|
Title |
Frontiers in Handwriting Recognition. International Conference on Frontiers in Handwriting Recognition. 18th International Conference, ICFHR 2022 |
Type |
Book Whole |
|
Year |
2022 |
Publication |
Frontiers in Handwriting Recognition. |
Abbreviated Journal |
|
|
|
Volume |
13639 |
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
ICFHR 2022, Hyderabad, India, December 4–7, 2022 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer |
Place of Publication |
|
Editor |
Utkarsh Porwal; Alicia Fornes; Faisal Shafait |
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-3-031-21648-0 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICFHR |
|
|
Notes |
DAG |
Approved |
no |
|
|
Call Number |
Admin @ si @ PFS2022 |
Serial |
3809 |
|
Permanent link to this record |
|
|
|
|
Author |
Asma Bensalah; Alicia Fornes; Cristina Carmona_Duarte; Josep Llados |
|
|
Title |
Easing Automatic Neurorehabilitation via Classification and Smoothness Analysis |
Type |
Conference Article |
|
Year |
2022 |
Publication |
Intertwining Graphonomics with Human Movements. 20th International Conference of the International Graphonomics Society, IGS 2022 |
Abbreviated Journal |
|
|
|
Volume |
13424 |
Issue |
|
Pages |
336-348 |
|
|
Keywords |
Neurorehabilitation; Upper-lim; Movement classification; Movement smoothness; Deep learning; Jerk |
|
|
Abstract |
Assessing the quality of movements for post-stroke patients during the rehabilitation phase is vital given that there is no standard stroke rehabilitation plan for all the patients. In fact, it depends basically on the patient’s functional independence and its progress along the rehabilitation sessions. To tackle this challenge and make neurorehabilitation more agile, we propose an automatic assessment pipeline that starts by recognising patients’ movements by means of a shallow deep learning architecture, then measuring the movement quality using jerk measure and related measures. A particularity of this work is that the dataset used is clinically relevant, since it represents movements inspired from Fugl-Meyer a well common upper-limb clinical stroke assessment scale for stroke patients. We show that it is possible to detect the contrast between healthy and patients movements in terms of smoothness, besides achieving conclusions about the patients’ progress during the rehabilitation sessions that correspond to the clinicians’ findings about each case. |
|
|
Address |
June 7-9, 2022, Las Palmas de Gran Canaria, Spain |
|
|
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 |
IGS |
|
|
Notes |
DAG; 600.121; 600.162; 602.230; 600.140 |
Approved |
no |
|
|
Call Number |
Admin @ si @ BFC2022 |
Serial |
3738 |
|
Permanent link to this record |
|
|
|
|
Author |
Josep Brugues Pujolras; Lluis Gomez; Dimosthenis Karatzas |
|
|
Title |
A Multilingual Approach to Scene Text Visual Question Answering |
Type |
Conference Article |
|
Year |
2022 |
Publication |
Document Analysis Systems.15th IAPR International Workshop, (DAS2022) |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
65-79 |
|
|
Keywords |
Scene text; Visual question answering; Multilingual word embeddings; Vision and language; Deep learning |
|
|
Abstract |
Scene Text Visual Question Answering (ST-VQA) has recently emerged as a hot research topic in Computer Vision. Current ST-VQA models have a big potential for many types of applications but lack the ability to perform well on more than one language at a time due to the lack of multilingual data, as well as the use of monolingual word embeddings for training. In this work, we explore the possibility to obtain bilingual and multilingual VQA models. In that regard, we use an already established VQA model that uses monolingual word embeddings as part of its pipeline and substitute them by FastText and BPEmb multilingual word embeddings that have been aligned to English. Our experiments demonstrate that it is possible to obtain bilingual and multilingual VQA models with a minimal loss in performance in languages not used during training, as well as a multilingual model trained in multiple languages that match the performance of the respective monolingual baselines. |
|
|
Address |
La Rochelle, France; May 22–25, 2022 |
|
|
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 |
DAS |
|
|
Notes |
DAG; 611.004; 600.155; 601.002 |
Approved |
no |
|
|
Call Number |
Admin @ si @ BGK2022b |
Serial |
3695 |
|
Permanent link to this record |
|
|
|
|
Author |
Adria Molina; Lluis Gomez; Oriol Ramos Terrades; Josep Llados |
|
|
Title |
A Generic Image Retrieval Method for Date Estimation of Historical Document Collections |
Type |
Conference Article |
|
Year |
2022 |
Publication |
Document Analysis Systems.15th IAPR International Workshop, (DAS2022) |
Abbreviated Journal |
|
|
|
Volume |
13237 |
Issue |
|
Pages |
583–597 |
|
|
Keywords |
Date estimation; Document retrieval; Image retrieval; Ranking loss; Smooth-nDCG |
|
|
Abstract |
Date estimation of historical document images is a challenging problem, with several contributions in the literature that lack of the ability to generalize from one dataset to others. This paper presents a robust date estimation system based in a retrieval approach that generalizes well in front of heterogeneous collections. We use a ranking loss function named smooth-nDCG to train a Convolutional Neural Network that learns an ordination of documents for each problem. One of the main usages of the presented approach is as a tool for historical contextual retrieval. It means that scholars could perform comparative analysis of historical images from big datasets in terms of the period where they were produced. We provide experimental evaluation on different types of documents from real datasets of manuscript and newspaper images. |
|
|
Address |
La Rochelle, France; May 22–25, 2022 |
|
|
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 |
DAS |
|
|
Notes |
DAG; 600.140; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ MGR2022 |
Serial |
3694 |
|
Permanent link to this record |
|
|
|
|
Author |
Henry Velesaca; Patricia Suarez; Dario Carpio; Rafael E. Rivadeneira; Angel Sanchez; Angel Morera |
|
|
Title |
Video Analytics in Urban Environments: Challenges and Approaches |
Type |
Book Chapter |
|
Year |
2022 |
Publication |
ICT Applications for Smart Cities |
Abbreviated Journal |
|
|
|
Volume |
224 |
Issue |
|
Pages |
101-121 |
|
|
Keywords |
|
|
|
Abstract |
This chapter reviews state-of-the-art approaches generally present in the pipeline of video analytics on urban scenarios. A typical pipeline is used to cluster approaches in the literature, including image preprocessing, object detection, object classification, and object tracking modules. Then, a review of recent approaches for each module is given. Additionally, applications and datasets generally used for training and evaluating the performance of these approaches are included. This chapter does not pretend to be an exhaustive review of state-of-the-art video analytics in urban environments but rather an illustration of some of the different recent contributions. The chapter concludes by presenting current trends in video analytics in the urban scenario field. |
|
|
Address |
September 2022 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
ISRL |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-3-031-06306-0 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
MSIAU; MACO |
Approved |
no |
|
|
Call Number |
Admin @ si @ VSC2022 |
Serial |
3811 |
|
Permanent link to this record |
|
|
|
|
Author |
Jorge Charco; Angel Sappa; Boris X. Vintimilla; Henry Velesaca |
|
|
Title |
Human Body Pose Estimation in Multi-view Environments |
Type |
Book Chapter |
|
Year |
2022 |
Publication |
ICT Applications for Smart Cities. Intelligent Systems Reference Library |
Abbreviated Journal |
|
|
|
Volume |
224 |
Issue |
|
Pages |
79-99 |
|
|
Keywords |
|
|
|
Abstract |
This chapter tackles the challenging problem of human pose estimation in multi-view environments to handle scenes with self-occlusions. The proposed approach starts by first estimating the camera pose—extrinsic parameters—in multi-view scenarios; due to few real image datasets, different virtual scenes are generated by using a special simulator, for training and testing the proposed convolutional neural network based approaches. Then, these extrinsic parameters are used to establish the relation between different cameras into the multi-view scheme, which captures the pose of the person from different points of view at the same time. The proposed multi-view scheme allows to robustly estimate human body joints’ position even in situations where they are occluded. This would help to avoid possible false alarms in behavioral analysis systems of smart cities, as well as applications for physical therapy, safe moving assistance for the elderly among other. The chapter concludes by presenting experimental results in real scenes by using state-of-the-art and the proposed multi-view approaches. |
|
|
Address |
September 2022 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
ISRL |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-3-031-06306-0 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
MSIAU; MACO |
Approved |
no |
|
|
Call Number |
Admin @ si @ CSV2022b |
Serial |
3810 |
|
Permanent link to this record |
|
|
|
|
Author |
Victoria Ruiz; Angel Sanchez; Jose F. Velez; Bogdan Raducanu |
|
|
Title |
Waste Classification with Small Datasets and Limited Resources |
Type |
Book Chapter |
|
Year |
2022 |
Publication |
ICT Applications for Smart Cities. Intelligent Systems Reference Library |
Abbreviated Journal |
|
|
|
Volume |
224 |
Issue |
|
Pages |
185-203 |
|
|
Keywords |
|
|
|
Abstract |
Automatic waste recycling has become a very important societal challenge nowadays, raising people’s awareness for a cleaner environment and a more sustainable lifestyle. With the transition to Smart Cities, and thanks to advanced ICT solutions, this problem has received a new impulse. The waste recycling focus has shifted from general waste treating facilities to an individual responsibility, where each person should become aware of selective waste separation. The surge of the mobile devices, accompanied by a significant increase in computation power, has potentiated and facilitated this individual role. An automated image-based waste classification mechanism can help with a more efficient recycling and a reduction of contamination from residuals. Despite the good results achieved with the deep learning methodologies for this task, the Achille’s heel is that they require large neural networks which need significant computational resources for training and therefore are not suitable for mobile devices. To circumvent this apparently intractable problem, we will rely on knowledge distillation in order to transfer the network’s knowledge from a larger network (called ‘teacher’) to a smaller, more compact one, (referred as ‘student’) and thus making it possible the task of image classification on a device with limited resources. For evaluation, we considered as ‘teachers’ large architectures such as InceptionResNet or DenseNet and as ‘students’, several configurations of the MobileNets. We used the publicly available TrashNet dataset to demonstrate that the distillation process does not significantly affect system’s performance (e.g. classification accuracy) of the student network. |
|
|
Address |
September 2022 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
ISRL |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-3-031-06306-0 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
LAMP |
Approved |
no |
|
|
Call Number |
Admin @ si @ |
Serial |
3813 |
|
Permanent link to this record |