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Author | Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera; Albert Clapes; Kamal Nasrollahi; Michael Holte; Thomas B. Moeslund | ||||
Title | Keep it Accurate and Diverse: Enhancing Action Recognition Performance by Ensemble Learning | Type | Conference Article | ||
Year | 2015 | Publication | IEEE Conference on Computer Vision and Pattern Recognition Worshops (CVPRW) | Abbreviated Journal | |
Volume | Issue | Pages | 22-29 | ||
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Abstract | The performance of different action recognition techniques has recently been studied by several computer vision researchers. However, the potential improvement in classification through classifier fusion by ensemble-based methods has remained unattended. In this work, we evaluate the performance of an ensemble of action learning techniques, each performing the recognition task from a different perspective.
The underlying idea is that instead of aiming a very sophisticated and powerful representation/learning technique, we can learn action categories using a set of relatively simple and diverse classifiers, each trained with different feature set. In addition, combining the outputs of several learners can reduce the risk of an unfortunate selection of a learner on an unseen action recognition scenario. This leads to having a more robust and general-applicable framework. In order to improve the recognition performance, a powerful combination strategy is utilized based on the Dempster-Shafer theory, which can effectively make use of diversity of base learners trained on different sources of information. The recognition results of the individual classifiers are compared with those obtained from fusing the classifiers’ output, showing enhanced performance of the proposed methodology. |
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Address | Boston; EEUU; June 2015 | ||||
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 | CVPRW | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ BGE2015 | Serial | 2655 | ||
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Author | Isabelle Guyon; Kristin Bennett; Gavin Cawley; Hugo Jair Escalante; Sergio Escalera; Tin Kam Ho; Nuria Macia; Bisakha Ray; Mehreen Saeed; Alexander Statnikov; Evelyne Viegas | ||||
Title | AutoML Challenge 2015: Design and First Results | Type | Conference Article | ||
Year | 2015 | Publication | 32nd International Conference on Machine Learning, ICML workshop, JMLR proceedings ICML15 | Abbreviated Journal | |
Volume | Issue | Pages | 1-8 | ||
Keywords | AutoML Challenge; machine learning; model selection; meta-learning; repre- sentation learning; active learning | ||||
Abstract | ChaLearn is organizing the Automatic Machine Learning (AutoML) contest 2015, which challenges participants to solve classication and regression problems without any human intervention. Participants' code is automatically run on the contest servers to train and test learning machines. However, there is no obligation to submit code; half of the prizes can be won by submitting prediction results only. Datasets of progressively increasing diculty are introduced throughout the six rounds of the challenge. (Participants can
enter the competition in any round.) The rounds alternate phases in which learners are tested on datasets participants have not seen (AutoML), and phases in which participants have limited time to tweak their algorithms on those datasets to improve performance (Tweakathon). This challenge will push the state of the art in fully automatic machine learning on a wide range of real-world problems. The platform will remain available beyond the termination of the challenge: http://codalab.org/AutoML. |
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Address | Lille; France; July 2015 | ||||
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 | ICML | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ GBC2015c | Serial | 2656 | ||
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Author | Victor Ponce; Hugo Jair Escalante; Sergio Escalera; Xavier Baro | ||||
Title | Gesture and Action Recognition by Evolved Dynamic Subgestures | Type | Conference Article | ||
Year | 2015 | Publication | 26th British Machine Vision Conference | Abbreviated Journal | |
Volume | Issue | Pages | 129.1-129.13 | ||
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Abstract | This paper introduces a framework for gesture and action recognition based on the evolution of temporal gesture primitives, or subgestures. Our work is inspired on the principle of producing genetic variations within a population of gesture subsequences, with the goal of obtaining a set of gesture units that enhance the generalization capability of standard gesture recognition approaches. In our context, gesture primitives are evolved over time using dynamic programming and generative models in order to recognize complex actions. In few generations, the proposed subgesture-based representation
of actions and gestures outperforms the state of the art results on the MSRDaily3D and MSRAction3D datasets. |
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Address | Swansea; uk; September 2015 | ||||
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 | HuPBA;MV | Approved | no | ||
Call Number | Admin @ si @ PEE2015 | Serial | 2657 | ||
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Author | Huamin Ren; Weifeng Liu; Soren Ingvor Olsen; Sergio Escalera; Thomas B. Moeslund | ||||
Title | Unsupervised Behavior-Specific Dictionary Learning for Abnormal Event Detection | Type | Conference Article | ||
Year | 2015 | Publication | 26th British Machine Vision Conference | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | |||||
Address | Swansea; uk; September 2015 | ||||
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 | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ RLO2015 | Serial | 2658 | ||
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Author | Eduardo Tusa; Arash Akbarinia; Raquel Gil Rodriguez; Corina Barbalata | ||||
Title | Real-Time Face Detection and Tracking Utilising OpenMP and ROS | Type | Conference Article | ||
Year | 2015 | Publication | 3rd Asia-Pacific Conference on Computer Aided System Engineering | Abbreviated Journal | |
Volume | Issue | Pages | 179 - 184 | ||
Keywords | RGB-D; Kinect; Human Detection and Tracking; ROS; OpenMP | ||||
Abstract | The first requisite of a robot to succeed in social interactions is accurate human localisation, i.e. subject detection and tracking. Later, it is estimated whether an interaction partner seeks attention, for example by interpreting the position and orientation of the body. In computer vision, these cues usually are obtained in colour images, whose qualities are degraded in ill illuminated social scenes. In these scenarios depth sensors offer a richer representation. Therefore, it is important to combine colour and depth information. The
second aspect that plays a fundamental role in the acceptance of social robots is their real-time-ability. Processing colour and depth images is computationally demanding. To overcome this we propose a parallelisation strategy of face detection and tracking based on two different architectures: message passing and shared memory. Our results demonstrate high accuracy in low computational time, processing nine times more number of frames in a parallel implementation. This provides a real-time social robot interaction. |
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Address | Quito; Ecuador; July 2015 | ||||
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 | APCASE | ||
Notes | NEUROBIT | Approved | no | ||
Call Number | Admin @ si @ TAG2015 | Serial | 2659 | ||
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Author | Arash Akbarinia; C. Alejandro Parraga | ||||
Title | Biologically Plausible Colour Naming Model | Type | Conference Article | ||
Year | 2015 | Publication | European Conference on Visual Perception ECVP2015 | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | Poster | ||||
Address | Liverpool; UK; August 2015 | ||||
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 | ECVP | ||
Notes | NEUROBIT; 600.068 | Approved | no | ||
Call Number | Admin @ si @ AkP2015 | Serial | 2660 | ||
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Author | Dennis G.Romero; Anselmo Frizera; Angel Sappa; Boris X. Vintimilla; Teodiano F.Bastos | ||||
Title | A predictive model for human activity recognition by observing actions and context | Type | Conference Article | ||
Year | 2015 | Publication | Advanced Concepts for Intelligent Vision Systems, Proceedings of 16th International Conference, ACIVS 2015 | Abbreviated Journal | |
Volume | 9386 | Issue | Pages | 323-333 | |
Keywords | |||||
Abstract | This paper presents a novel model to estimate human activities — a human activity is defined by a set of human actions. The proposed approach is based on the usage of Recurrent Neural Networks (RNN) and Bayesian inference through the continuous monitoring of human actions and its surrounding environment. In the current work human activities are inferred considering not only visual analysis but also additional resources; external sources of information, such as context information, are incorporated to contribute to the activity estimation. The novelty of the proposed approach lies in the way the information is encoded, so that it can be later associated according to a predefined semantic structure. Hence, a pattern representing a given activity can be defined by a set of actions, plus contextual information or other kind of information that could be relevant to describe the activity. Experimental results with real data are provided showing the validity of the proposed approach. | ||||
Address | Catania; Italy; October 2015 | ||||
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 | 978-3-319-25902-4 | Medium | |
Area | Expedition | Conference | ACIVS | ||
Notes | ADAS; 600.076 | Approved | no | ||
Call Number | Admin @ si @ RFS2015 | Serial | 2661 | ||
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Author | Miguel Oliveira; Victor Santos; Angel Sappa; P. Dias | ||||
Title | Scene Representations for Autonomous Driving: an approach based on polygonal primitives | Type | Conference Article | ||
Year | 2015 | Publication | 2nd Iberian Robotics Conference ROBOT2015 | Abbreviated Journal | |
Volume | 417 | Issue | Pages | 503-515 | |
Keywords | Scene reconstruction; Point cloud; Autonomous vehicles | ||||
Abstract | In this paper, we present a novel methodology to compute a 3D scene
representation. The algorithm uses macro scale polygonal primitives to model the scene. This means that the representation of the scene is given as a list of large scale polygons that describe the geometric structure of the environment. Results show that the approach is capable of producing accurate descriptions of the scene. In addition, the algorithm is very efficient when compared to other techniques. |
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Address | Lisboa; Portugal; November 2015 | ||||
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 | ROBOT | ||
Notes | ADAS; 600.076; 600.086 | Approved | no | ||
Call Number | Admin @ si @ OSS2015a | Serial | 2662 | ||
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Author | J.Poujol; Cristhian A. Aguilera-Carrasco; E.Danos; Boris X. Vintimilla; Ricardo Toledo; Angel Sappa | ||||
Title | Visible-Thermal Fusion based Monocular Visual Odometry | Type | Conference Article | ||
Year | 2015 | Publication | 2nd Iberian Robotics Conference ROBOT2015 | Abbreviated Journal | |
Volume | 417 | Issue | Pages | 517-528 | |
Keywords | Monocular Visual Odometry; LWIR-RGB cross-spectral Imaging; Image Fusion. | ||||
Abstract | The manuscript evaluates the performance of a monocular visual odometry approach when images from different spectra are considered, both independently and fused. The objective behind this evaluation is to analyze if classical approaches can be improved when the given images, which are from different spectra, are fused and represented in new domains. The images in these new domains should have some of the following properties: i) more robust to noisy data; ii) less sensitive to changes (e.g., lighting); iii) more rich in descriptive information, among other. In particular in the current work two different image fusion strategies are considered. Firstly, images from the visible and thermal spectrum are fused using a Discrete Wavelet Transform (DWT) approach. Secondly, a monochrome threshold strategy is considered. The obtained
representations are evaluated under a visual odometry framework, highlighting their advantages and disadvantages, using different urban and semi-urban scenarios. Comparisons with both monocular-visible spectrum and monocular-infrared spectrum, are also provided showing the validity of the proposed approach. |
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Address | Lisboa; Portugal; November 2015 | ||||
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 | 2194-5357 | ISBN | 978-3-319-27145-3 | Medium | |
Area | Expedition | Conference | ROBOT | ||
Notes | ADAS; 600.076; 600.086 | Approved | no | ||
Call Number | Admin @ si @ PAD2015 | Serial | 2663 | ||
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Author | Miguel Oliveira; L. Seabra Lopes; G. Hyun Lim; S. Hamidreza Kasaei; Angel Sappa; A. Tom | ||||
Title | Concurrent Learning of Visual Codebooks and Object Categories in Openended Domains | Type | Conference Article | ||
Year | 2015 | Publication | International Conference on Intelligent Robots and Systems | Abbreviated Journal | |
Volume | Issue | Pages | 2488 - 2495 | ||
Keywords | Visual Learning; Computer Vision; Autonomous Agents | ||||
Abstract | In open-ended domains, robots must continuously learn new object categories. When the training sets are created offline, it is not possible to ensure their representativeness with respect to the object categories and features the system will find when operating online. In the Bag of Words model, visual codebooks are constructed from training sets created offline. This might lead to non-discriminative visual words and, as a consequence, to poor recognition performance. This paper proposes a visual object recognition system which concurrently learns in an incremental and online fashion both the visual object category representations as well as the codebook words used to encode them. The codebook is defined using Gaussian Mixture Models which are updated using new object views. The approach contains similarities with the human visual object recognition system: evidence suggests that the development of recognition capabilities occurs on multiple levels and is sustained over large periods of time. Results show that the proposed system with concurrent learning of object categories and codebooks is capable of learning more categories, requiring less examples, and with similar accuracies, when compared to the classical Bag of Words approach using offline constructed codebooks. | ||||
Address | Hamburg; Germany; October 2015 | ||||
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 | IROS | ||
Notes | ADAS; 600.076 | Approved | no | ||
Call Number | Admin @ si @ OSL2015 | Serial | 2664 | ||
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Author | Adria Ruiz; Joost Van de Weijer; Xavier Binefa | ||||
Title | From emotions to action units with hidden and semi-hidden-task learning | Type | Conference Article | ||
Year | 2015 | Publication | 16th IEEE International Conference on Computer Vision | Abbreviated Journal | |
Volume | Issue | Pages | 3703-3711 | ||
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Abstract | Limited annotated training data is a challenging problem in Action Unit recognition. In this paper, we investigate how the use of large databases labelled according to the 6 universal facial expressions can increase the generalization ability of Action Unit classifiers. For this purpose, we propose a novel learning framework: Hidden-Task Learning. HTL aims to learn a set of Hidden-Tasks (Action Units)for which samples are not available but, in contrast, training data is easier to obtain from a set of related VisibleTasks (Facial Expressions). To that end, HTL is able to exploit prior knowledge about the relation between Hidden and Visible-Tasks. In our case, we base this prior knowledge on empirical psychological studies providing statistical correlations between Action Units and universal facial expressions. Additionally, we extend HTL to Semi-Hidden Task Learning (SHTL) assuming that Action Unit training samples are also provided. Performing exhaustive experiments over four different datasets, we show that HTL and SHTL improve the generalization ability of AU classifiers by training them with additional facial expression data. Additionally, we show that SHTL achieves competitive performance compared with state-of-the-art Transductive Learning approaches which face the problem of limited training data by using unlabelled test samples during training. | ||||
Address | Santiago de Chile; Chile; December 2015 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ICCV | ||
Notes | LAMP; 600.068; 600.079 | Approved | no | ||
Call Number | Admin @ si @ RWB2015 | Serial | 2671 | ||
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Author | Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Michael Felsberg; J.Laaksonen | ||||
Title | Deep semantic pyramids for human attributes and action recognition | Type | Conference Article | ||
Year | 2015 | Publication | Image Analysis, Proceedings of 19th Scandinavian Conference , SCIA 2015 | Abbreviated Journal | |
Volume | 9127 | Issue | Pages | 341-353 | |
Keywords | Action recognition; Human attributes; Semantic pyramids | ||||
Abstract | Describing persons and their actions is a challenging problem due to variations in pose, scale and viewpoint in real-world images. Recently, semantic pyramids approach [1] for pose normalization has shown to provide excellent results for gender and action recognition. The performance of semantic pyramids approach relies on robust image description and is therefore limited due to the use of shallow local features. In the context of object recognition [2] and object detection [3], convolutional neural networks (CNNs) or deep features have shown to improve the performance over the conventional shallow features.
We propose deep semantic pyramids for human attributes and action recognition. The method works by constructing spatial pyramids based on CNNs of different part locations. These pyramids are then combined to obtain a single semantic representation. We validate our approach on the Berkeley and 27 Human Attributes datasets for attributes classification. For action recognition, we perform experiments on two challenging datasets: Willow and PASCAL VOC 2010. The proposed deep semantic pyramids provide a significant gain of 17.2%, 13.9%, 24.3% and 22.6% compared to the standard shallow semantic pyramids on Berkeley, 27 Human Attributes, Willow and PASCAL VOC 2010 datasets respectively. Our results also show that deep semantic pyramids outperform conventional CNNs based on the full bounding box of the person. Finally, we compare our approach with state-of-the-art methods and show a gain in performance compared to best methods in literature. |
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Address | Denmark; Copenhagen; June 2015 | ||||
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 | 978-3-319-19664-0 | Medium | |
Area | Expedition | Conference | SCIA | ||
Notes | LAMP; 600.068; 600.079;ADAS | Approved | no | ||
Call Number | Admin @ si @ KRW2015b | Serial | 2672 | ||
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Author | Marta Nuñez-Garcia; Sonja Simpraga; M.Angeles Jurado; Maite Garolera; Roser Pueyo; Laura Igual | ||||
Title | FADR: Functional-Anatomical Discriminative Regions for rest fMRI Characterization | Type | Conference Article | ||
Year | 2015 | Publication | Machine Learning in Medical Imaging, Proceedings of 6th International Workshop, MLMI 2015, Held in Conjunction with MICCAI 2015 | Abbreviated Journal | |
Volume | Issue | Pages | 61-68 | ||
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Abstract | |||||
Address | Munich; Germany; October 2015 | ||||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | MLMI | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ NSJ2015 | Serial | 2674 | ||
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Author | Chen Zhang; Maria del Mar Vila Muñoz; Petia Radeva; Roberto Elosua; Maria Grau; Angels Betriu; Elvira Fernandez-Giraldez; Laura Igual | ||||
Title | Carotid Artery Segmentation in Ultrasound Images | Type | Conference Article | ||
Year | 2015 | Publication | Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting (CVII-STENT2015), Joint MICCAI Workshops | Abbreviated Journal | |
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Address | Munich; Germany; October 2015 | ||||
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Area | Expedition | Conference | CVII-STENT | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ ZVR2015 | Serial | 2675 | ||
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Author | Onur Ferhat; Arcadi Llanza; Fernando Vilariño | ||||
Title | Gaze interaction for multi-display systems using natural light eye-tracker | Type | Conference Article | ||
Year | 2015 | Publication | 2nd International Workshop on Solutions for Automatic Gaze Data Analysis | Abbreviated Journal | |
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Address | Bielefeld; Germany; September 2015 | ||||
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Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | SAGA | ||
Notes | MV;SIAI | Approved | no | ||
Call Number | Admin @ si @ FLV2015b | Serial | 2676 | ||
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