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Author Muhammad Anwer Rao edit  openurl
  Title Color for Object Detection and Action Recognition Type Book Whole
  Year 2013 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords (up)  
  Abstract Recognizing object categories in real world images is a challenging problem in computer vision. The deformable part based framework is currently the most successful approach for object detection. Generally, HOG are used for image representation within the part-based framework. For action recognition, the bag-of-word framework has shown to provide promising results. Within the bag-of-words framework, local image patches are described by SIFT descriptor. Contrary to object detection and action recognition, combining color and shape has shown to provide the best performance for object and scene recognition.

In the first part of this thesis, we analyze the problem of person detection in still images. Standard person detection approaches rely on intensity based features for image representation while ignoring the color. Channel based descriptors is one of the most commonly used approaches in object recognition. This inspires us to evaluate incorporating color information using the channel based fusion approach for the task of person detection.

In the second part of the thesis, we investigate the problem of object detection in still images. Due to high dimensionality, channel based fusion increases the computational cost. Moreover, channel based fusion has been found to obtain inferior results for object category where one of the visual varies significantly. On the other hand, late fusion is known to provide improved results for a wide range of object categories. A consequence of late fusion strategy is the need of a pure color descriptor. Therefore, we propose to use Color attributes as an explicit color representation for object detection. Color attributes are compact and computationally efficient. Consequently color attributes are combined with traditional shape features providing excellent results for object detection task.

Finally, we focus on the problem of action detection and classification in still images. We investigate the potential of color for action classification and detection in still images. We also evaluate different fusion approaches for combining color and shape information for action recognition. Additionally, an analysis is performed to validate the contribution of color for action recognition. Our results clearly demonstrate that combining color and shape information significantly improve the performance of both action classification and detection in still images.
 
  Address Barcelona  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Editor Antonio Lopez;Joost Van de Weijer  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number Admin @ si @ Rao2013 Serial 2281  
Permanent link to this record
 

 
Author Javier Marin edit  openurl
  Title Pedestrian Detection Based on Local Experts Type Book Whole
  Year 2013 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords (up)  
  Abstract During the last decade vision-based human detection systems have started to play a key rolein multiple applications linked to driver assistance, surveillance, robot sensing and home automation.
Detecting humans is by far one of the most challenging tasks in Computer Vision.
This is mainly due to the high degree of variability in the human appearanceassociated to
the clothing, pose, shape and size. Besides, other factors such as cluttered scenarios, partial occlusions, or environmental conditions can make the detection task even harder.
Most promising methods of the state-of-the-art rely on discriminative learning paradigms which are fed with positive and negative examples. The training data is one of the most
relevant elements in order to build a robust detector as it has to cope the large variability of the target. In order to create this dataset human supervision is required. The drawback at this point is the arduous effort of annotating as well as looking for such claimed variability.
In this PhD thesis we address two recurrent problems in the literature. In the first stage,we aim to reduce the consuming task of annotating, namely, by using computer graphics.
More concretely, we develop a virtual urban scenario for later generating a pedestrian dataset.
Then, we train a detector using this dataset, and finally we assess if this detector can be successfully applied in a real scenario.
In the second stage, we focus on increasing the robustness of our pedestrian detectors
under partial occlusions. In particular, we present a novel occlusion handling approach to increase the performance of block-based holistic methods under partial occlusions. For this purpose, we make use of local experts via a RandomSubspaceMethod (RSM) to handle these cases. If the method infers a possible partial occlusion, then the RSM, based on performance statistics obtained from partially occluded data, is applied. The last objective of this thesis
is to propose a robust pedestrian detector based on an ensemble of local experts. To achieve this goal, we use the random forest paradigm, where the trees act as ensembles an their nodesare the local experts. In particular, each expert focus on performing a robust classification ofa pedestrian body patch. This approach offers computational efficiency and far less design complexity when compared to other state-of-the-artmethods, while reaching better accuracy
 
  Address Barcelona  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Editor Antonio Lopez;Jaume Amores  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number Admin @ si @ Mar2013 Serial 2280  
Permanent link to this record
 

 
Author Wenjuan Gong edit  openurl
  Title 3D Motion Data aided Human Action Recognition and Pose Estimation Type Book Whole
  Year 2013 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords (up)  
  Abstract In this work, we explore human action recognition and pose estimation prob-
lems. Different from traditional works of learning from 2D images or video
sequences and their annotated output, we seek to solve the problems with ad-
ditional 3D motion capture information, which helps to fill the gap between 2D
image features and human interpretations.
We first compare two different schools of approaches commonly used for 3D
pose estimation from 2D pose configuration: modeling and learning methods.
By looking into experiments results and considering our problems, we fixed a
learning method as the following approaches to do pose estimation. We then
establish a framework by adding a module of detecting 2D pose configuration
from images with varied background, which widely extend the application of
the approach. We also seek to directly estimate 3D poses from image features,
instead of estimating 2D poses as a intermediate module. We explore a robust
input feature, which combined with the proposed distance measure, provides
a solution for noisy or corrupted inputs. We further utilize the above method
to estimate weak poses,which is a concise representation of the original poses
by using dimension deduction technologies, from image features. Weak pose
space is where we calculate vocabulary and label action types using a bog of
words pipeline. Temporal information of an action is taken into consideration by
considering several consecutive frames as a single unit for computing vocabulary
and histogram assignments.
 
  Address Barcelona  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Editor Jordi Gonzalez;Xavier Roca  
  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 @ Gon2013 Serial 2279  
Permanent link to this record
 

 
Author Murad Al Haj edit  openurl
  Title Looking at Faces: Detection, Tracking and Pose Estimation Type Book Whole
  Year 2013 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords (up)  
  Abstract Humans can effortlessly perceive faces, follow them over space and time, and decode their rich content, such as pose, identity and expression. However, despite many decades of research on automatic facial perception in areas like face detection, expression recognition, pose estimation and face recognition, and despite many successes, a complete solution remains elusive. This thesis is dedicated to three problems in automatic face perception, namely face detection, face tracking and pose estimation.

In face detection, an initial simple model is presented that uses pixel-based heuristics to segment skin locations and hand-crafted rules to determine the locations of the faces present in an image. Different colorspaces are studied to judge whether a colorspace transformation can aid skin color detection. The output of this study is used in the design of a more complex face detector that is able to successfully generalize to different scenarios.

In face tracking, a framework that combines estimation and control in a joint scheme is presented to track a face with a single pan-tilt-zoom camera. While this work is mainly motivated by tracking faces, it can be easily applied atop of any detector to track different objects. The applicability of this method is demonstrated on simulated as well as real-life scenarios.

The last and most important part of this thesis is dedicate to monocular head pose estimation. In this part, a method based on partial least squares (PLS) regression is proposed to estimate pose and solve the alignment problem simultaneously. The contributions of this work are two-fold: 1) demonstrating that the proposed method achieves better than state-of-the-art results on the estimation problem and 2) developing a technique to reduce misalignment based on the learned PLS factors that outperform multiple instance learning (MIL) without the need for any re-training or the inclusion of misaligned samples in the training process, as normally done in MIL.
 
  Address Barcelona  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Editor Jordi Gonzalez;Xavier Roca  
  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 @ Haj2013 Serial 2278  
Permanent link to this record
 

 
Author Albert Gordo edit  openurl
  Title Document Image Representation, Classification and Retrieval in Large-Scale Domains Type Book Whole
  Year 2013 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords (up)  
  Abstract Despite the “paperless office” ideal that started in the decade of the seventies, businesses still strive against an increasing amount of paper documentation. Companies still receive huge amounts of paper documentation that need to be analyzed and processed, mostly in a manual way. A solution for this task consists in, first, automatically scanning the incoming documents. Then, document images can be analyzed and information can be extracted from the data. Documents can also be automatically dispatched to the appropriate workflows, used to retrieve similar documents in the dataset to transfer information, etc.

Due to the nature of this “digital mailroom”, we need document representation methods to be general, i.e., able to cope with very different types of documents. We need the methods to be sound, i.e., able to cope with unexpected types of documents, noise, etc. And, we need to methods to be scalable, i.e., able to cope with thousands or millions of documents that need to be processed, stored, and consulted. Unfortunately, current techniques of document representation, classification and retrieval are not apt for this digital mailroom framework, since they do not fulfill some or all of these requirements.

Through this thesis we focus on the problem of document representation aimed at classification and retrieval tasks under this digital mailroom framework. We first propose a novel document representation based on runlength histograms, and extend it to cope with more complex documents such as multiple-page documents, or documents that contain more sources of information such as extracted OCR text. Then we focus on the scalability requirements and propose a novel binarization method which we dubbed PCAE, as well as two general asymmetric distances between binary embeddings that can significantly improve the retrieval results at a minimal extra computational cost. Finally, we note the importance of supervised learning when performing large-scale retrieval, and study several approaches that can significantly boost the results at no extra cost at query time.
 
  Address Barcelona  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Editor Ernest Valveny;Florent Perronnin  
  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 @ Gor2013 Serial 2277  
Permanent link to this record
 

 
Author Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados edit  url
doi  isbn
openurl 
  Title Multilevel Analysis of Attributed Graphs for Explicit Graph Embedding in Vector Spaces Type Book Chapter
  Year 2013 Publication Graph Embedding for Pattern Analysis Abbreviated Journal  
  Volume Issue Pages 1-26  
  Keywords (up)  
  Abstract Ability to recognize patterns is among the most crucial capabilities of human beings for their survival, which enables them to employ their sophisticated neural and cognitive systems [1], for processing complex audio, visual, smell, touch, and taste signals. Man is the most complex and the best existing system of pattern recognition. Without any explicit thinking, we continuously compare, classify, and identify huge amount of signal data everyday [2], starting from the time we get up in the morning till the last second we fall asleep. This includes recognizing the face of a friend in a crowd, a spoken word embedded in noise, the proper key to lock the door, smell of coffee, the voice of a favorite singer, the recognition of alphabetic characters, and millions of more tasks that we perform on regular basis.  
  Address  
  Corporate Author Thesis  
  Publisher Springer New York Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-4614-4456-5 Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number Admin @ si @ LRL2013b Serial 2271  
Permanent link to this record
 

 
Author Isabel Guitart; Jordi Conesa; Luis Villarejo; Agata Lapedriza; David Masip; Antoni Perez; Elena Planas edit   pdf
doi  isbn
openurl 
  Title Opinion Mining on Educational Resources at the Open University of Catalonia Type Conference Article
  Year 2013 Publication 3rd International Workshop on Adaptive Learning via Interactive, Collaborative and Emotional approaches. In conjunction with CISIS 2013: The 7th International Conference on Complex, Intelligent, and Software Intensive Systems Abbreviated Journal  
  Volume Issue Pages 385 - 390  
  Keywords (up)  
  Abstract In order to make improvements to teaching, it is vital to know what students think of the way they are taught. With that purpose in mind, exhaustively analyzing the forums associated with the subjects taught at the Universitat Oberta de Cataluya (UOC) would be extremely helpful, as the university's students often post comments on their learning experiences in them. Exploiting the content of such forums is not a simple undertaking. The volume of data involved is very large, and performing the task manually would require a great deal of effort from lecturers. As a first step to solve this problem, we propose a tool to automatically analyze the posts in forums of communities of UOC students and teachers, with a view to systematically mining the opinions they contain. This article defines the architecture of such tool and explains how lexical-semantic and language technology resources can be used to that end. For pilot testing purposes, the tool has been used to identify students' opinions on the UOC's Business Intelligence master's degree course during the last two years. The paper discusses the results of such test. The contribution of this paper is twofold. Firstly, it demonstrates the feasibility of using natural language parsing techniques to help teachers to make decisions. Secondly, it introduces a simple tool that can be refined and adapted to a virtual environment for the purpose in question.  
  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 978-0-7695-4992-7 Medium  
  Area Expedition Conference ALICE  
  Notes OR;MV Approved no  
  Call Number GCV2013 Serial 2268  
Permanent link to this record
 

 
Author Shida Beigpour edit  openurl
  Title Illumination and object reflectance modeling Type Book Whole
  Year 2013 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords (up)  
  Abstract More realistic and accurate models of the scene illumination and object reflectance can greatly improve the quality of many computer vision and computer graphics tasks. Using such model, a more profound knowledge about the interaction of light with object surfaces can be established which proves crucial to a variety of computer vision applications. In the current work, we investigate the various existing approaches to illumination and reflectance modeling and form an analysis on their shortcomings in capturing the complexity of real-world scenes. Based on this analysis we propose improvements to different aspects of reflectance and illumination estimation in order to more realistically model the real-world scenes in the presence of complex lighting phenomena (i.e, multiple illuminants, interreflections and shadows). Moreover, we captured our own multi-illuminant dataset which consists of complex scenes and illumination conditions both outdoor and in laboratory conditions. In addition we investigate the use of synthetic data to facilitate the construction of datasets and improve the process of obtaining ground-truth information.  
  Address Barcelona  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Editor Joost Van de Weijer;Ernest Valveny  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes CIC Approved no  
  Call Number Admin @ si @ Bei2013 Serial 2267  
Permanent link to this record
 

 
Author Abel Gonzalez-Garcia; Robert Benavente; Olivier Penacchio; Javier Vazquez; Maria Vanrell; C. Alejandro Parraga edit   pdf
doi  isbn
openurl 
  Title Coloresia: An Interactive Colour Perception Device for the Visually Impaired Type Book Chapter
  Year 2013 Publication Multimodal Interaction in Image and Video Applications Abbreviated Journal  
  Volume 48 Issue Pages 47-66  
  Keywords (up)  
  Abstract A significative percentage of the human population suffer from impairments in their capacity to distinguish or even see colours. For them, everyday tasks like navigating through a train or metro network map becomes demanding. We present a novel technique for extracting colour information from everyday natural stimuli and presenting it to visually impaired users as pleasant, non-invasive sound. This technique was implemented inside a Personal Digital Assistant (PDA) portable device. In this implementation, colour information is extracted from the input image and categorised according to how human observers segment the colour space. This information is subsequently converted into sound and sent to the user via speakers or headphones. In the original implementation, it is possible for the user to send its feedback to reconfigure the system, however several features such as these were not implemented because the current technology is limited.We are confident that the full implementation will be possible in the near future as PDA technology improves.  
  Address  
  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 1868-4394 ISBN 978-3-642-35931-6 Medium  
  Area Expedition Conference  
  Notes CIC; 600.052; 605.203 Approved no  
  Call Number Admin @ si @ GBP2013 Serial 2266  
Permanent link to this record
 

 
Author Shida Beigpour; Marc Serra; Joost Van de Weijer; Robert Benavente; Maria Vanrell; Olivier Penacchio; Dimitris Samaras edit   pdf
doi  openurl
  Title Intrinsic Image Evaluation On Synthetic Complex Scenes Type Conference Article
  Year 2013 Publication 20th IEEE International Conference on Image Processing Abbreviated Journal  
  Volume Issue Pages 285 - 289  
  Keywords (up)  
  Abstract Scene decomposition into its illuminant, shading, and reflectance intrinsic images is an essential step for scene understanding. Collecting intrinsic image groundtruth data is a laborious task. The assumptions on which the ground-truth
procedures are based limit their application to simple scenes with a single object taken in the absence of indirect lighting and interreflections. We investigate synthetic data for intrinsic image research since the extraction of ground truth is straightforward, and it allows for scenes in more realistic situations (e.g, multiple illuminants and interreflections). With this dataset we aim to motivate researchers to further explore intrinsic image decomposition in complex scenes.
 
  Address Melbourne; Australia; September 2013  
  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 ICIP  
  Notes CIC; 600.048; 600.052; 600.051 Approved no  
  Call Number Admin @ si @ BSW2013 Serial 2264  
Permanent link to this record
 

 
Author Rahat Khan; Joost Van de Weijer; Fahad Shahbaz Khan; Damien Muselet; christophe Ducottet; Cecile Barat edit   pdf
doi  openurl
  Title Discriminative Color Descriptors Type Conference Article
  Year 2013 Publication IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 2866 - 2873  
  Keywords (up)  
  Abstract Color description is a challenging task because of large variations in RGB values which occur due to scene accidental events, such as shadows, shading, specularities, illuminant color changes, and changes in viewing geometry. Traditionally, this challenge has been addressed by capturing the variations in physics-based models, and deriving invariants for the undesired variations. The drawback of this approach is that sets of distinguishable colors in the original color space are mapped to the same value in the photometric invariant space. This results in a drop of discriminative power of the color description. In this paper we take an information theoretic approach to color description. We cluster color values together based on their discriminative power in a classification problem. The clustering has the explicit objective to minimize the drop of mutual information of the final representation. We show that such a color description automatically learns a certain degree of photometric invariance. We also show that a universal color representation, which is based on other data sets than the one at hand, can obtain competing performance. Experiments show that the proposed descriptor outperforms existing photometric invariants. Furthermore, we show that combined with shape description these color descriptors obtain excellent results on four challenging datasets, namely, PASCAL VOC 2007, Flowers-102, Stanford dogs-120 and Birds-200.  
  Address Portland; Oregon; June 2013  
  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 1063-6919 ISBN Medium  
  Area Expedition Conference CVPR  
  Notes CIC; 600.048 Approved no  
  Call Number Admin @ si @ KWK2013a Serial 2262  
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Author Christophe Rigaud; Dimosthenis Karatzas; Joost Van de Weijer; Jean-Christophe Burie; Jean-Marc Ogier edit   pdf
doi  openurl
  Title An active contour model for speech balloon detection in comics Type Conference Article
  Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 1240-1244  
  Keywords (up)  
  Abstract Comic books constitute an important cultural heritage asset in many countries. Digitization combined with subsequent comic book understanding would enable a variety of new applications, including content-based retrieval and content retargeting. Document understanding in this domain is challenging as comics are semi-structured documents, combining semantically important graphical and textual parts. Few studies have been done in this direction. In this work we detail a novel approach for closed and non-closed speech balloon localization in scanned comic book pages, an essential step towards a fully automatic comic book understanding. The approach is compared with existing methods for closed balloon localization found in the literature and results are presented.  
  Address washington; USA; August 2013  
  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 1520-5363 ISBN Medium  
  Area Expedition Conference ICDAR  
  Notes DAG; CIC; 600.056 Approved no  
  Call Number Admin @ si @ RKW2013a Serial 2260  
Permanent link to this record
 

 
Author Francesco Ciompi; Simone Balocco; Carles Caus; J. Mauri; Petia Radeva edit  doi
isbn  openurl
  Title Stent shape estimation through a comprehensive interpretation of intravascular ultrasound images Type Conference Article
  Year 2013 Publication 16th International Conference on Medical Image Computing and Computer Assisted Intervention Abbreviated Journal  
  Volume 8150 Issue 2 Pages 345-352  
  Keywords (up)  
  Abstract We present a method for automatic struts detection and stent shape estimation in cross-sectional intravascular ultrasound images. A stent shape is first estimated through a comprehensive interpretation of the vessel morphology, performed using a supervised context-aware multi-class classification scheme. Then, the successive strut identification exploits both local appearance and the defined stent shape. The method is tested on 589 images obtained from 80 patients, achieving a F-measure of 74.1% and an averaged distance between manual and automatic struts of 0.10 mm.  
  Address Nagoya; Japan; September 2013  
  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 978-3-642-40762-8 Medium  
  Area Expedition Conference MICCAI  
  Notes MILAB Approved no  
  Call Number Admin @ si @ CBC2013 Serial 2258  
Permanent link to this record
 

 
Author Laura Igual; Xavier Baro edit   pdf
openurl 
  Title Experiencia de aprendizaje de programación basada en proyectos. Simposio-Taller Estrategias y herramientas para el aprendizaje y la evaluación Type Miscellaneous
  Year 2013 Publication Simposio-Taller Estrategias y herramientas para el aprendizaje y la evaluación, de las XIX Jornadas sobre la Enseñanza Universitaria de la Informática Abbreviated Journal  
  Volume Issue Pages  
  Keywords (up)  
  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 JENUI  
  Notes OR;HuPBA;MV Approved no  
  Call Number Admin @ si @ IgB2013 Serial 2257  
Permanent link to this record
 

 
Author Vitaliy Konovalov; Albert Clapes; Sergio Escalera edit   pdf
openurl 
  Title Automatic Hand Detection in RGB-Depth Data Sequences Type Conference Article
  Year 2013 Publication 16th Catalan Conference on Artificial Intelligence Abbreviated Journal  
  Volume Issue Pages 91-100  
  Keywords (up)  
  Abstract Detecting hands in multi-modal RGB-Depth visual data has become a challenging Computer Vision problem with several applications of interest. This task involves dealing with changes in illumination, viewpoint variations, the articulated nature of the human body, the high flexibility of the wrist articulation, and the deformability of the hand itself. In this work, we propose an accurate and efficient automatic hand detection scheme to be applied in Human-Computer Interaction (HCI) applications in which the user is seated at the desk and, thus, only the upper body is visible. Our main hypothesis is that hand landmarks remain at a nearly constant geodesic distance from an automatically located anatomical reference point.
In a given frame, the human body is segmented first in the depth image. Then, a
graph representation of the body is built in which the geodesic paths are computed from the reference point. The dense optical flow vectors on the corresponding RGB image are used to reduce ambiguities of the geodesic paths’ connectivity, allowing to eliminate false edges interconnecting different body parts. Finally, we are able to detect the position of both hands based on invariant geodesic distances and optical flow within the body region, without involving costly learning procedures.
 
  Address Vic; October 2013  
  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 CCIA  
  Notes HuPBA;MILAB Approved no  
  Call Number Admin @ si @ KCE2013 Serial 2323  
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