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| Author | Ferran Diego; Jose Manuel Alvarez; Joan Serrat; Antonio Lopez | ||||
| Title | Vision-based road detection via on-line video registration | Type | Conference Article | ||
| Year | 2010 | Publication | 13th Annual International Conference on Intelligent Transportation Systems | Abbreviated Journal | |
| Volume | Issue | Pages | 1135–1140 | ||
| Keywords | video alignment; road detection | ||||
| Abstract | TB6.2
Road segmentation is an essential functionality for supporting advanced driver assistance systems (ADAS) such as road following and vehicle and pedestrian detection. Significant efforts have been made in order to solve this task using vision-based techniques. The major challenge is to deal with lighting variations and the presence of objects on the road surface. In this paper, we propose a new road detection method to infer the areas of the image depicting road surfaces without performing any image segmentation. The idea is to previously segment manually or semi-automatically the road region in a traffic-free reference video record on a first drive. And then to transfer these regions to the frames of a second video sequence acquired later in a second drive through the same road, in an on-line manner. This is possible because we are able to automatically align the two videos in time and space, that is, to synchronize them and warp each frame of the first video to its corresponding frame in the second one. The geometric transform can thus transfer the road region to the present frame on-line. In order to reduce the different lighting conditions which are present in outdoor scenarios, our approach incorporates a shadowless feature space which represents an image in an illuminant-invariant feature space. Furthermore, we propose a dynamic background subtraction algorithm which removes the regions containing vehicles in the observed frames which are within the transferred road region. |
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| Address | Madeira Island (Portugal) | ||||
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
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Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2153-0009 | ISBN | 978-1-4244-7657-2 | Medium | |
| Area | Expedition | Conference | ITSC | ||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ DAS2010 | Serial | 1424 | ||
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| Author | Diego Alejandro Cheda; Daniel Ponsa; Antonio Lopez | ||||
| Title | Camera Egomotion Estimation in the ADAS Context | Type | Conference Article | ||
| Year | 2010 | Publication | 13th International IEEE Annual Conference on Intelligent Transportation Systems | Abbreviated Journal | |
| Volume | Issue | Pages | 1415–1420 | ||
| Keywords | |||||
| Abstract | Camera-based Advanced Driver Assistance Systems (ADAS) have concentrated many research efforts in the last decades. Proposals based on monocular cameras require the knowledge of the camera pose with respect to the environment, in order to reach an efficient and robust performance. A common assumption in such systems is considering the road as planar, and the camera pose with respect to it as approximately known. However, in real situations, the camera pose varies along time due to the vehicle movement, the road slope, and irregularities on the road surface. Thus, the changes in the camera position and orientation (i.e., the egomotion) are critical information that must be estimated at every frame to avoid poor performances. This work focuses on egomotion estimation from a monocular camera under the ADAS context. We review and compare egomotion methods with simulated and real ADAS-like sequences. Basing on the results of our experiments, we show which of the considered nonlinear and linear algorithms have the best performance in this domain. | ||||
| Address | Madeira Island (Portugal) | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
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Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2153-0009 | ISBN | 978-1-4244-7657-2 | Medium | |
| Area | Expedition | Conference | ITSC | ||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ CPL2010 | Serial | 1425 | ||
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| Author | Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu | ||||
| Title | Perceptual color texture codebooks for retrieving in highly diverse texture datasets | Type | Conference Article | ||
| Year | 2010 | Publication | 20th International Conference on Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 866–869 | ||
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| Abstract | Color and texture are visual cues of different nature, their integration in a useful visual descriptor is not an obvious step. One way to combine both features is to compute texture descriptors independently on each color channel. A second way is integrate the features at a descriptor level, in this case arises the problem of normalizing both cues. A significant progress in the last years in object recognition has provided the bag-of-words framework that again deals with the problem of feature combination through the definition of vocabularies of visual words. Inspired in this framework, here we present perceptual textons that will allow to fuse color and texture at the level of p-blobs, which is our feature detection step. Feature representation is based on two uniform spaces representing the attributes of the p-blobs. The low-dimensionality of these text on spaces will allow to bypass the usual problems of previous approaches. Firstly, no need for normalization between cues; and secondly, vocabularies are directly obtained from the perceptual properties of text on spaces without any learning step. Our proposal improve current state-of-art of color-texture descriptors in an image retrieval experiment over a highly diverse texture dataset from Corel. | ||||
| Address | Istanbul (Turkey) | ||||
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
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Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1051-4651 | ISBN | 978-1-4244-7542-1 | Medium | |
| Area | Expedition | Conference | ICPR | ||
| Notes | CIC | Approved | no | ||
| Call Number | CAT @ cat @ ASV2010b | Serial | 1426 | ||
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| Author | Sergio Escalera; Petia Radeva; Jordi Vitria; Xavier Baro; Bogdan Raducanu | ||||
| Title | Modelling and Analyzing Multimodal Dyadic Interactions Using Social Networks | Type | Conference Article | ||
| Year | 2010 | Publication | 12th International Conference on Multimodal Interfaces and 7th Workshop on Machine Learning for Multimodal Interaction. | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | Social interaction; Multimodal fusion, Influence model; Social network analysis | ||||
| Abstract | Social network analysis became a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from
multimodal dyadic interactions. First, speech detection is performed through an audio/visual fusion scheme based on stacked sequential learning. In the audio domain, speech is detected through clusterization of audio features. Clusters are modelled by means of an One-state Hidden Markov Model containing a diagonal covariance Gaussian Mixture Model. In the visual domain, speech detection is performed through differential-based feature extraction from the segmented mouth region, and a dynamic programming matching procedure. Second, in order to model the dyadic interactions, we employed the Influence Model whose states encode the previous integrated audio/visual data. Third, the social network is extracted based on the estimated influences. For our study, we used a set of videos belonging to New York Times’ Blogging Heads opinion blog. The results are reported both in terms of accuracy of the audio/visual data fusion and centrality measures used to characterize the social network. |
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| Address | Beijing (China) | ||||
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| Area | Expedition | Conference | ICMI-MLI | ||
| Notes | OR;MILAB;HUPBA;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ ERV2010 | Serial | 1427 | ||
| Permanent link to this record | |||||
| Author | Jose Manuel Alvarez; Felipe Lumbreras; Theo Gevers; Antonio Lopez | ||||
| Title | Geographic Information for vision-based Road Detection | Type | Conference Article | ||
| Year | 2010 | Publication | IEEE Intelligent Vehicles Symposium | Abbreviated Journal | |
| Volume | Issue | Pages | 621–626 | ||
| Keywords | road detection | ||||
| Abstract | Road detection is a vital task for the development of autonomous vehicles. The knowledge of the free road surface ahead of the target vehicle can be used for autonomous driving, road departure warning, as well as to support advanced driver assistance systems like vehicle or pedestrian detection. Using vision to detect the road has several advantages in front of other sensors: richness of features, easy integration, low cost or low power consumption. Common vision-based road detection approaches use low-level features (such as color or texture) as visual cues to group pixels exhibiting similar properties. However, it is difficult to foresee a perfect clustering algorithm since roads are in outdoor scenarios being imaged from a mobile platform. In this paper, we propose a novel high-level approach to vision-based road detection based on geographical information. The key idea of the algorithm is exploiting geographical information to provide a rough detection of the road. Then, this segmentation is refined at low-level using color information to provide the final result. The results presented show the validity of our approach. | ||||
| Address | San Diego; CA; USA | ||||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | IV | ||
| Notes | ADAS;ISE | Approved | no | ||
| Call Number | ADAS @ adas @ ALG2010 | Serial | 1428 | ||
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| Author | Jaume Amores; David Geronimo; Antonio Lopez | ||||
| Title | Multiple instance and active learning for weakly-supervised object-class segmentation | Type | Conference Article | ||
| Year | 2010 | Publication | 3rd IEEE International Conference on Machine Vision | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | Multiple Instance Learning; Active Learning; Object-class segmentation. | ||||
| Abstract | In object-class segmentation, one of the most tedious tasks is to manually segment many object examples in order to learn a model of the object category. Yet, there has been little research on reducing the degree of manual annotation for
object-class segmentation. In this work we explore alternative strategies which do not require full manual segmentation of the object in the training set. In particular, we study the use of bounding boxes as a coarser and much cheaper form of segmentation and we perform a comparative study of several Multiple-Instance Learning techniques that allow to obtain a model with this type of weak annotation. We show that some of these methods can be competitive, when used with coarse segmentations, with methods that require full manual segmentation of the objects. Furthermore, we show how to use active learning combined with this weakly supervised strategy. As we see, this strategy permits to reduce the amount of annotation and optimize the number of examples that require full manual segmentation in the training set. |
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| Address | Hong-Kong | ||||
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| Language | Summary Language | Original Title | |||
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| Area | Expedition | Conference | ICMV | ||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ AGL2010b | Serial | 1429 | ||
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| Author | Joan Serrat; Antonio Lopez | ||||
| Title | Deteccion automatica de lineas de carril para la asistencia a la conduccion | Type | Miscellaneous | ||
| Year | 2010 | Publication | UAB Divulga – Revista de divulgacion cientifica | Abbreviated Journal | |
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| Abstract | La detección por cámara de las líneas de carril en las carreteras puede ser una solución asequible a los riesgos de conducción generados por los adelantamientos o las salidas de carril. Este trabajo propone un sistema que funciona en tiempo real y que obtiene muy buenos resultados. El sistema está preparado para identificar las líneas en condiciones de visibilidad poco favorables, como puede ser la conducción nocturna o con otros vehículos que dificulten la visión. | ||||
| Address | Bellaterra (Spain) | ||||
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| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ SeL2010 | Serial | 1430 | ||
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| Author | Albert Gordo; Jaume Gibert; Ernest Valveny; Marçal Rusiñol | ||||
| Title | A Kernel-based Approach to Document Retrieval | Type | Conference Article | ||
| Year | 2010 | Publication | 9th IAPR International Workshop on Document Analysis Systems | Abbreviated Journal | |
| Volume | Issue | Pages | 377–384 | ||
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| Abstract | In this paper we tackle the problem of document image retrieval by combining a similarity measure between documents and the probability that a given document belongs to a certain class. The membership probability to a specific class is computed using Support Vector Machines in conjunction with similarity measure based kernel applied to structural document representations. In the presented experiments, we use different document representations, both visual and structural, and we apply them to a database of historical documents. We show how our method based on similarity kernels outperforms the usual distance-based retrieval. | ||||
| Address | Boston; USA; | ||||
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| Language | Summary Language | Original Title | |||
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Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-60558-773-8 | Medium | ||
| Area | Expedition | Conference | DAS | ||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ GGV2010 | Serial | 1431 | ||
| Permanent link to this record | |||||
| Author | Antonio Clavelli; Dimosthenis Karatzas; Josep Llados | ||||
| Title | A framework for the assessment of text extraction algorithms on complex colour images | Type | Conference Article | ||
| Year | 2010 | Publication | 9th IAPR International Workshop on Document Analysis Systems | Abbreviated Journal | |
| Volume | Issue | Pages | 19–26 | ||
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| Abstract | The availability of open, ground-truthed datasets and clear performance metrics is a crucial factor in the development of an application domain. The domain of colour text image analysis (real scenes, Web and spam images, scanned colour documents) has traditionally suffered from a lack of a comprehensive performance evaluation framework. Such a framework is extremely difficult to specify, and corresponding pixel-level accurate information tedious to define. In this paper we discuss the challenges and technical issues associated with developing such a framework. Then, we describe a complete framework for the evaluation of text extraction methods at multiple levels, provide a detailed ground-truth specification and present a case study on how this framework can be used in a real-life situation. | ||||
| Address | Boston; USA; | ||||
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| Language | Summary Language | Original Title | |||
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Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-60558-773-8 | Medium | ||
| Area | Expedition | Conference | DAS | ||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ CKL2010 | Serial | 1432 | ||
| Permanent link to this record | |||||
| Author | Partha Pratim Roy; Umapada Pal; Josep Llados | ||||
| Title | Query Driven Word Retrieval in Graphical Documents | Type | Conference Article | ||
| Year | 2010 | Publication | 9th IAPR International Workshop on Document Analysis Systems | Abbreviated Journal | |
| Volume | Issue | Pages | 191–198 | ||
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| Abstract | In this paper, we present an approach towards the retrieval of words from graphical document images. In graphical documents, due to presence of multi-oriented characters in non-structured layout, word indexing is a challenging task. The proposed approach uses recognition results of individual components to form character pairs with the neighboring components. An indexing scheme is designed to store the spatial description of components and to access them efficiently. Given a query text word (ascii/unicode format), the character pairs present in it are searched in the document. Next the retrieved character pairs are linked sequentially to form character string. Dynamic programming is applied to find different instances of query words. A string edit distance is used here to match the query word as the objective function. Recognition of multi-scale and multi-oriented character component is done using Support Vector Machine classifier. To consider multi-oriented character strings the features used in the SVM are invariant to character orientation. Experimental results show that the method is efficient to locate a query word from multi-oriented text in graphical documents. | ||||
| Address | Boston; USA | ||||
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
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Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-60558-773-8 | Medium | ||
| Area | Expedition | Conference | DAS | ||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ RPL2010b | Serial | 1433 | ||
| Permanent link to this record | |||||
| Author | Marçal Rusiñol; Josep Llados | ||||
| Title | Efficient Logo Retrieval Through Hashing Shape Context Descriptors | Type | Conference Article | ||
| Year | 2010 | Publication | 9th IAPR International Workshop on Document Analysis Systems | Abbreviated Journal | |
| Volume | Issue | Pages | 215–222 | ||
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| Abstract | In this paper, we present an approach towards the retrieval of words from graphical document images. In graphical documents, due to presence of multi-oriented characters in non-structured layout, word indexing is a challenging task. The proposed approach uses recognition results of individual components to form character pairs with the neighboring components. An indexing scheme is designed to store the spatial description of components and to access them efficiently. Given a query text word (ascii/unicode format), the character pairs present in it are searched in the document. Next the retrieved character pairs are linked sequentially to form character string. Dynamic programming is applied to find different instances of query words. A string edit distance is used here to match the query word as the objective function. Recognition of multi-scale and multi-oriented character component is done using Support Vector Machine classifier. To consider multi-oriented character strings the features used in the SVM are invariant to character orientation. Experimental results show that the method is efficient to locate a query word from multi-oriented text in graphical documents. | ||||
| Address | Boston; USA | ||||
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| Area | Expedition | Conference | DAS | ||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ RuL2010b | Serial | 1434 | ||
| Permanent link to this record | |||||
| Author | Marçal Rusiñol; Farshad Nourbakhsh; Dimosthenis Karatzas; Ernest Valveny; Josep Llados | ||||
| Title | Perceptual Image Retrieval by Adding Color Information to the Shape Context Descriptor | Type | Conference Article | ||
| Year | 2010 | Publication | 20th International Conference on Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 1594–1597 | ||
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| Abstract | In this paper we present a method for the retrieval of images in terms of perceptual similarity. Local color information is added to the shape context descriptor in order to obtain an object description integrating both shape and color as visual cues. We use a color naming algorithm in order to represent the color information from a perceptual point of view. The proposed method has been tested in two different applications, an object retrieval scenario based on color sketch queries and a color trademark retrieval problem. Experimental results show that the addition of the color information significantly outperforms the sole use of the shape context descriptor. | ||||
| Address | Istanbul (Turkey) | ||||
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| Language | Summary Language | Original Title | |||
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Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1051-4651 | ISBN | 978-1-4244-7542-1 | Medium | |
| Area | Expedition | Conference | ICPR | ||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ RNK2010 | Serial | 1435 | ||
| Permanent link to this record | |||||
| Author | Farshad Nourbakhsh; Dimosthenis Karatzas; Ernest Valveny | ||||
| Title | A polar-based logo representation based on topological and colour features | Type | Conference Article | ||
| Year | 2010 | Publication | 9th IAPR International Workshop on Document Analysis Systems | Abbreviated Journal | |
| Volume | Issue | Pages | 341–348 | ||
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| Abstract | In this paper, we propose a novel rotation and scale invariant method for colour logo retrieval and classification, which involves performing a simple colour segmentation and subsequently describing each of the resultant colour components based on a set of topological and colour features. A polar representation is used to represent the logo and the subsequent logo matching is based on Cyclic Dynamic Time Warping (CDTW). We also show how combining information about the global distribution of the logo components and their local neighbourhood using the Delaunay triangulation allows to improve the results. All experiments are performed on a dataset of 2500 instances of 100 colour logo images in different rotations and scales. | ||||
| Address | Boston; USA; | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-60558-773-8 | Medium | ||
| Area | Expedition | Conference | DAS | ||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ NKV2010 | Serial | 1436 | ||
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| Author | Sebastien Mace; Herve Locteau; Ernest Valveny; Salvatore Tabbone | ||||
| Title | A system to detect rooms in architectural floor plan images | Type | Conference Article | ||
| Year | 2010 | Publication | 9th IAPR International Workshop on Document Analysis Systems | Abbreviated Journal | |
| Volume | Issue | Pages | 167–174 | ||
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| Abstract | In this article, a system to detect rooms in architectural floor plan images is described. We first present a primitive extraction algorithm for line detection. It is based on an original coupling of classical Hough transform with image vectorization in order to perform robust and efficient line detection. We show how the lines that satisfy some graphical arrangements are combined into walls. We also present the way we detect some door hypothesis thanks to the extraction of arcs. Walls and door hypothesis are then used by our room segmentation strategy; it consists in recursively decomposing the image until getting nearly convex regions. The notion of convexity is difficult to quantify, and the selection of separation lines between regions can also be rough. We take advantage of knowledge associated to architectural floor plans in order to obtain mostly rectangular rooms. Qualitative and quantitative evaluations performed on a corpus of real documents show promising results. | ||||
| Address | Boston; USA | ||||
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| Language | Summary Language | Original Title | |||
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Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-60558-773-8 | Medium | ||
| Area | Expedition | Conference | DAS | ||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ MLV2010 | Serial | 1437 | ||
| Permanent link to this record | |||||
| Author | Marco Pedersoli; Jordi Gonzalez; Andrew Bagdanov; Juan J. Villanueva | ||||
| Title | Recursive Coarse-to-Fine Localization for fast Object Recognition | Type | Conference Article | ||
| Year | 2010 | Publication | 11th European Conference on Computer Vision | Abbreviated Journal | |
| Volume | 6313 | Issue | II | Pages | 280–293 |
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| Abstract | Cascading techniques are commonly used to speed-up the scan of an image for object detection. However, cascades of detectors are slow to train due to the high number of detectors and corresponding thresholds to learn. Furthermore, they do not use any prior knowledge about the scene structure to decide where to focus the search. To handle these problems, we propose a new way to scan an image, where we couple a recursive coarse-to-fine refinement together with spatial constraints of the object location. For doing that we split an image into a set of uniformly distributed neighborhood regions, and for each of these we apply a local greedy search over feature resolutions. The neighborhood is defined as a scanning region that only one object can occupy. Therefore the best hypothesis is obtained as the location with maximum score and no thresholds are needed. We present an implementation of our method using a pyramid of HOG features and we evaluate it on two standard databases, VOC2007 and INRIA dataset. Results show that the Recursive Coarse-to-Fine Localization (RCFL) achieves a 12x speed-up compared to standard sliding windows. Compared with a cascade of multiple resolutions approach our method has slightly better performance in speed and Average-Precision. Furthermore, in contrast to cascading approach, the speed-up is independent of image conditions, the number of detected objects and clutter. | ||||
| Address | Crete (Greece) | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-15566-6 | Medium | |
| Area | Expedition | Conference | ECCV | ||
| Notes | ISE | Approved | no | ||
| Call Number | DAG @ dag @ PGB2010 | Serial | 1438 | ||
| Permanent link to this record | |||||