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Author | German Ros; Sebastian Ramos; Manuel Granados; Amir Bakhtiary; David Vazquez; Antonio Lopez | ||||
Title | Vision-based Offline-Online Perception Paradigm for Autonomous Driving | Type | Conference Article | ||
Year | 2015 | Publication | IEEE Winter Conference on Applications of Computer Vision | Abbreviated Journal | |
Volume | Issue ![]() |
Pages | 231 - 238 | ||
Keywords | Autonomous Driving; Scene Understanding; SLAM; Semantic Segmentation | ||||
Abstract | Autonomous driving is a key factor for future mobility. Properly perceiving the environment of the vehicles is essential for a safe driving, which requires computing accurate geometric and semantic information in real-time. In this paper, we challenge state-of-the-art computer vision algorithms for building a perception system for autonomous driving. An inherent drawback in the computation of visual semantics is the trade-off between accuracy and computational cost. We propose to circumvent this problem by following an offline-online strategy. During the offline stage dense 3D semantic maps are created. In the online stage the current driving area is recognized in the maps via a re-localization process, which allows to retrieve the pre-computed accurate semantics and 3D geometry in realtime. Then, detecting the dynamic obstacles we obtain a rich understanding of the current scene. We evaluate quantitatively our proposal in the KITTI dataset and discuss the related open challenges for the computer vision community. | ||||
Address | Hawaii; January 2015 | ||||
Corporate Author | Thesis | ||||
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Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | ACDC | Expedition | Conference | WACV | |
Notes | ADAS; 600.076 | Approved | no | ||
Call Number | ADAS @ adas @ RRG2015 | Serial | 2499 | ||
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Author | Jorge Bernal; Debora Gil; Carles Sanchez; F. Javier Sanchez | ||||
Title | Discarding Non Informative Regions for Efficient Colonoscopy Image Analysis | Type | Conference Article | ||
Year | 2014 | Publication | 1st MICCAI Workshop on Computer-Assisted and Robotic Endoscopy | Abbreviated Journal | |
Volume | 8899 | Issue ![]() |
Pages | 1-10 | |
Keywords | Image Segmentation; Polyps, Colonoscopy; Valley Information; Energy Maps | ||||
Abstract | In this paper we present a novel polyp region segmentation method for colonoscopy videos. Our method uses valley information associated to polyp boundaries in order to provide an initial segmentation. This first segmentation is refined to eliminate boundary discontinuities caused by image artifacts or other elements of the scene. Experimental results over a publicly annotated database show that our method outperforms both general and specific segmentation methods by providing more accurate regions rich in polyp content. We also prove how image preprocessing is needed to improve final polyp region segmentation. | ||||
Address | Boston; USA; September 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 | 978-3-319-13409-3 | Medium | |
Area | Expedition | Conference | CARE | ||
Notes | MV; IAM; 600.044; 600.047; 600.060; 600.075 | Approved | no | ||
Call Number | Admin @ si @ BGS2014b | Serial | 2503 | ||
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Author | Joan M. Nuñez; Jorge Bernal; Miquel Ferrer; Fernando Vilariño | ||||
Title | Impact of Keypoint Detection on Graph-based Characterization of Blood Vessels in Colonoscopy Videos | Type | Conference Article | ||
Year | 2014 | Publication | CARE workshop | Abbreviated Journal | |
Volume | Issue ![]() |
Pages | |||
Keywords | Colonoscopy; Graph Matching; Biometrics; Vessel; Intersection | ||||
Abstract | We explore the potential of the use of blood vessels as anatomical landmarks for developing image registration methods in colonoscopy images. An unequivocal representation of blood vessels could be used to guide follow-up methods to track lesions over different interventions. We propose a graph-based representation to characterize network structures, such as blood vessels, based on the use of intersections and endpoints. We present a study consisting of the assessment of the minimal performance a keypoint detector should achieve so that the structure can still be recognized. Experimental results prove that, even by achieving a loss of 35% of the keypoints, the descriptive power of the associated graphs to the vessel pattern is still high enough to recognize blood vessels. | ||||
Address | Boston; USA; September 2014 | ||||
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 | CARE | ||
Notes | MV; DAG; 600.060; 600.047; 600.077;SIAI | Approved | no | ||
Call Number | Admin @ si @ NBF2014 | Serial | 2504 | ||
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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. | ||||
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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 | ||
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Author | Marc Serra; Olivier Penacchio; Robert Benavente; Maria Vanrell; Dimitris Samaras | ||||
Title | The Photometry of Intrinsic Images | Type | Conference Article | ||
Year | 2014 | Publication | 27th IEEE Conference on Computer Vision and Pattern Recognition | Abbreviated Journal | |
Volume | Issue ![]() |
Pages | 1494-1501 | ||
Keywords | |||||
Abstract | Intrinsic characterization of scenes is often the best way to overcome the illumination variability artifacts that complicate most computer vision problems, from 3D reconstruction to object or material recognition. This paper examines the deficiency of existing intrinsic image models to accurately account for the effects of illuminant color and sensor characteristics in the estimation of intrinsic images and presents a generic framework which incorporates insights from color constancy research to the intrinsic image decomposition problem. The proposed mathematical formulation includes information about the color of the illuminant and the effects of the camera sensors, both of which modify the observed color of the reflectance of the objects in the scene during the acquisition process. By modeling these effects, we get a “truly intrinsic” reflectance image, which we call absolute reflectance, which is invariant to changes of illuminant or camera sensors. This model allows us to represent a wide range of intrinsic image decompositions depending on the specific assumptions on the geometric properties of the scene configuration and the spectral properties of the light source and the acquisition system, thus unifying previous models in a single general framework. We demonstrate that even partial information about sensors improves significantly the estimated reflectance images, thus making our method applicable for a wide range of sensors. We validate our general intrinsic image framework experimentally with both synthetic data and natural images. | ||||
Address | Columbus; Ohio; USA; June 2014 | ||||
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 | CVPR | ||
Notes | CIC; 600.052; 600.051; 600.074 | Approved | no | ||
Call Number | Admin @ si @ SPB2014 | Serial | 2506 | ||
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Author | M. Danelljan; Fahad Shahbaz Khan; Michael Felsberg; Joost Van de Weijer | ||||
Title | Adaptive color attributes for real-time visual tracking | Type | Conference Article | ||
Year | 2014 | Publication | 27th IEEE Conference on Computer Vision and Pattern Recognition | Abbreviated Journal | |
Volume | Issue ![]() |
Pages | 1090 - 1097 | ||
Keywords | |||||
Abstract | Visual tracking is a challenging problem in computer vision. Most state-of-the-art visual trackers either rely on luminance information or use simple color representations for image description. Contrary to visual tracking, for object
recognition and detection, sophisticated color features when combined with luminance have shown to provide excellent performance. Due to the complexity of the tracking problem, the desired color feature should be computationally efficient, and possess a certain amount of photometric invariance while maintaining high discriminative power. This paper investigates the contribution of color in a tracking-by-detection framework. Our results suggest that color attributes provides superior performance for visual tracking. We further propose an adaptive low-dimensional variant of color attributes. Both quantitative and attributebased evaluations are performed on 41 challenging benchmark color sequences. The proposed approach improves the baseline intensity-based tracker by 24% in median distance precision. Furthermore, we show that our approach outperforms state-of-the-art tracking methods while running at more than 100 frames per second. |
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Address | Nottingham; UK; September 2014 | ||||
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 | CVPR | ||
Notes | CIC; LAMP; 600.074; 600.079 | Approved | no | ||
Call Number | Admin @ si @ DKF2014 | Serial | 2509 | ||
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Author | C. Alejandro Parraga | ||||
Title | Color Vision, Computational Methods for | Type | Book Chapter | ||
Year | 2014 | Publication | Encyclopedia of Computational Neuroscience | Abbreviated Journal | |
Volume | Issue ![]() |
Pages | 1-11 | ||
Keywords | Color computational vision; Computational neuroscience of color | ||||
Abstract | The study of color vision has been aided by a whole battery of computational methods that attempt to describe the mechanisms that lead to our perception of colors in terms of the information-processing properties of the visual system. Their scope is highly interdisciplinary, linking apparently dissimilar disciplines such as mathematics, physics, computer science, neuroscience, cognitive science, and psychology. Since the sensation of color is a feature of our brains, computational approaches usually include biological features of neural systems in their descriptions, from retinal light-receptor interaction to subcortical color opponency, cortical signal decoding, and color categorization. They produce hypotheses that are usually tested by behavioral or psychophysical experiments. | ||||
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Publisher | Springer-Verlag Berlin Heidelberg | Place of Publication | Editor | Dieter Jaeger; Ranu Jung | |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-1-4614-7320-6 | Medium | ||
Area | Expedition | Conference | |||
Notes | CIC; 600.074 | Approved | no | ||
Call Number | Admin @ si @ Par2014 | Serial | 2512 | ||
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Author | Adriana Romero; Carlo Gatta; Gustavo Camps-Valls | ||||
Title | Unsupervised Deep Feature Extraction Of Hyperspectral Images | Type | Conference Article | ||
Year | 2014 | Publication | 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing | Abbreviated Journal | |
Volume | Issue ![]() |
Pages | |||
Keywords | Convolutional networks; deep learning; sparse learning; feature extraction; hyperspectral image classification | ||||
Abstract | This paper presents an effective unsupervised sparse feature learning algorithm to train deep convolutional networks on hyperspectral images. Deep convolutional hierarchical representations are learned and then used for pixel classification. Features in lower layers present less abstract representations of data, while higher layers represent more abstract and complex characteristics. We successfully illustrate the performance of the extracted representations in a challenging AVIRIS hyperspectral image classification problem, compared to standard dimensionality reduction methods like principal component analysis (PCA) and its kernel counterpart (kPCA). The proposed method largely outperforms the previous state-ofthe-art results on the same experimental setting. Results show that single layer networks can extract powerful discriminative features only when the receptive field accounts for neighboring pixels. Regarding the deep architecture, we can conclude that: (1) additional layers in a deep architecture significantly improve the performance w.r.t. single layer variants; (2) the max-pooling step in each layer is mandatory to achieve satisfactory results; and (3) the performance gain w.r.t. the number of layers is upper bounded, since the spatial resolution is reduced at each pooling, resulting in too spatially coarse output features. | ||||
Address | Lausanne; Switzerland; June 2014 | ||||
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 | WHISPERS | ||
Notes | MILAB; LAMP; 600.079 | Approved | no | ||
Call Number | Admin @ si @ RGC2014 | Serial | 2513 | ||
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Author | P. Wang; V. Eglin; C. Garcia; C. Largeron; Josep Llados; Alicia Fornes | ||||
Title | A Coarse-to-Fine Word Spotting Approach for Historical Handwritten Documents Based on Graph Embedding and Graph Edit Distance | Type | Conference Article | ||
Year | 2014 | Publication | 22nd International Conference on Pattern Recognition | Abbreviated Journal | |
Volume | Issue ![]() |
Pages | 3074 - 3079 | ||
Keywords | word spotting; coarse-to-fine mechamism; graphbased representation; graph embedding; graph edit distance | ||||
Abstract | Effective information retrieval on handwritten document images has always been a challenging task, especially historical ones. In the paper, we propose a coarse-to-fine handwritten word spotting approach based on graph representation. The presented model comprises both the topological and morphological signatures of the handwriting. Skeleton-based graphs with the Shape Context labelled vertexes are established for connected components. Each word image is represented as a sequence of graphs. Aiming at developing a practical and efficient word spotting approach for large-scale historical handwritten documents, a fast and coarse comparison is first applied to prune the regions that are not similar to the query based on the graph embedding methodology. Afterwards, the query and regions of interest are compared by graph edit distance based on the Dynamic Time Warping alignment. The proposed approach is evaluated on a public dataset containing 50 pages of historical marriage license records. The results show that the proposed approach achieves a compromise between efficiency and accuracy. | ||||
Address | Stockholm; Sweden; August 2014 | ||||
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 | 1051-4651 | ISBN | Medium | ||
Area | Expedition | Conference | ICPR | ||
Notes | DAG; 600.061; 602.006; 600.077 | Approved | no | ||
Call Number | Admin @ si @ WEG2014a | Serial | 2515 | ||
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Author | Alicia Fornes; Josep Llados; Joan Mas; Joana Maria Pujadas-Mora; Anna Cabre | ||||
Title | A Bimodal Crowdsourcing Platform for Demographic Historical Manuscripts | Type | Conference Article | ||
Year | 2014 | Publication | Digital Access to Textual Cultural Heritage Conference | Abbreviated Journal | |
Volume | Issue ![]() |
Pages | 103-108 | ||
Keywords | |||||
Abstract | In this paper we present a crowdsourcing web-based application for extracting information from demographic handwritten document images. The proposed application integrates two points of view: the semantic information for demographic research, and the ground-truthing for document analysis research. Concretely, the application has the contents view, where the information is recorded into forms, and the labeling view, with the word labels for evaluating document analysis techniques. The crowdsourcing architecture allows to accelerate the information extraction (many users can work simultaneously), validate the information, and easily provide feedback to the users. We finally show how the proposed application can be extended to other kind of demographic historical manuscripts. | ||||
Address | Madrid; May 2014 | ||||
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 | 978-1-4503-2588-2 | Medium | ||
Area | Expedition | Conference | DATeCH | ||
Notes | DAG; 600.061; 602.006; 600.077 | Approved | no | ||
Call Number | Admin @ si @ FLM2014 | Serial | 2516 | ||
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Author | P. Wang; V. Eglin; C. Garcia; C. Largeron; Josep Llados; Alicia Fornes | ||||
Title | A Novel Learning-free Word Spotting Approach Based on Graph Representation | Type | Conference Article | ||
Year | 2014 | Publication | 11th IAPR International Workshop on Document Analysis and Systems | Abbreviated Journal | |
Volume | Issue ![]() |
Pages | 207-211 | ||
Keywords | |||||
Abstract | Effective information retrieval on handwritten document images has always been a challenging task. In this paper, we propose a novel handwritten word spotting approach based on graph representation. The presented model comprises both topological and morphological signatures of handwriting. Skeleton-based graphs with the Shape Context labelled vertexes are established for connected components. Each word image is represented as a sequence of graphs. In order to be robust to the handwriting variations, an exhaustive merging process based on DTW alignment result is introduced in the similarity measure between word images. With respect to the computation complexity, an approximate graph edit distance approach using bipartite matching is employed for graph matching. The experiments on the George Washington dataset and the marriage records from the Barcelona Cathedral dataset demonstrate that the proposed approach outperforms the state-of-the-art structural methods. | ||||
Address | Tours; France; April 2014 | ||||
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 | 978-1-4799-3243-6 | Medium | ||
Area | Expedition | Conference | DAS | ||
Notes | DAG; 600.061; 602.006; 600.077 | Approved | no | ||
Call Number | Admin @ si @ WEG2014b | Serial | 2517 | ||
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Author | Claudio Baecchi; Francesco Turchini; Lorenzo Seidenari; Andrew Bagdanov; Alberto del Bimbo | ||||
Title | Fisher vectors over random density forest for object recognition | Type | Conference Article | ||
Year | 2014 | Publication | 22nd International Conference on Pattern Recognition | Abbreviated Journal | |
Volume | Issue ![]() |
Pages | 4328-4333 | ||
Keywords | |||||
Abstract | |||||
Address | Stockholm; Sweden; August 2014 | ||||
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 | ICPR | ||
Notes | LAMP; 600.079 | Approved | no | ||
Call Number | Admin @ si @ BTS2014 | Serial | 2518 | ||
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Author | Federico Bartoli; Giuseppe Lisanti; Svebor Karaman; Andrew Bagdanov; Alberto del Bimbo | ||||
Title | Unsupervised scene adaptation for faster multi- scale pedestrian detection | Type | Conference Article | ||
Year | 2014 | Publication | 22nd International Conference on Pattern Recognition | Abbreviated Journal | |
Volume | Issue ![]() |
Pages | 3534 - 3539 | ||
Keywords | |||||
Abstract | |||||
Address | Stockholm; Sweden; August 2014 | ||||
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 | ICPR | ||
Notes | LAMP; 600.079 | Approved | no | ||
Call Number | Admin @ si @ BLK2014 | Serial | 2519 | ||
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Author | Svebor Karaman; Giuseppe Lisanti; Andrew Bagdanov; Alberto del Bimbo | ||||
Title | From re-identification to identity inference: Labeling consistency by local similarity constraints | Type | Book Chapter | ||
Year | 2014 | Publication | Person Re-Identification | Abbreviated Journal | |
Volume | 2 | Issue ![]() |
Pages | 287-307 | |
Keywords | re-identification; Identity inference; Conditional random fields; Video surveillance | ||||
Abstract | In this chapter, we introduce the problem of identity inference as a generalization of person re-identification. It is most appropriate to distinguish identity inference from re-identification in situations where a large number of observations must be identified without knowing a priori that groups of test images represent the same individual. The standard single- and multishot person re-identification common in the literature are special cases of our formulation. We present an approach to solving identity inference by modeling it as a labeling problem in a Conditional Random Field (CRF). The CRF model ensures that the final labeling gives similar labels to detections that are similar in feature space. Experimental results are given on the ETHZ, i-LIDS and CAVIAR datasets. Our approach yields state-of-the-art performance for multishot re-identification, and our results on the more general identity inference problem demonstrate that we are able to infer the identity of very many examples even with very few labeled images in the gallery. | ||||
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Publisher | Springer London | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | 2191-6586 | ISBN | 978-1-4471-6295-7 | Medium | |
Area | Expedition | Conference | |||
Notes | LAMP; 600.079 | Approved | no | ||
Call Number | Admin @ si @KLB2014b | Serial | 2521 | ||
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Author | Antonio Hernandez; Stan Sclaroff; Sergio Escalera | ||||
Title | Contextual rescoring for Human Pose Estimation | Type | Conference Article | ||
Year | 2014 | Publication | 25th British Machine Vision Conference | Abbreviated Journal | |
Volume | Issue ![]() |
Pages | |||
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Abstract | A contextual rescoring method is proposed for improving the detection of body joints of a pictorial structure model for human pose estimation. A set of mid-level parts is incorporated in the model, and their detections are used to extract spatial and score-related features relative to other body joint hypotheses. A technique is proposed for the automatic discovery of a compact subset of poselets that covers a set of validation images
while maximizing precision. A rescoring mechanism is defined as a set-based boosting classifier that computes a new score for body joint detections, given its relationship to detections of other body joints and mid-level parts in the image. This new score complements the unary potential of a discriminatively trained pictorial structure model. Experiments on two benchmarks show performance improvements when considering the proposed mid-level image representation and rescoring approach in comparison with other pictorial structure-based approaches. |
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Address | Nottingham; UK; 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 | BMVC | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | HSE2014 | Serial | 2525 | ||
Permanent link to this record |