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| Author | Jordi Vitria; Joao Sanchez; Miguel Raposo; Mario Hernandez | ||||
Title  |
Pattern Recognition and Image Analysis | Type | Book Whole | ||
| Year | 2011 | Publication | 5th Iberian Conference Pattern Recognition and Image Analysis | Abbreviated Journal | |
| Volume | 6669 | Issue | Pages | ||
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| Address | Las Palmas de Gran Canaria. Spain | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer-Verlag | Place of Publication | Berlin | Editor | J. Vitrià; J. Sanchez; M. Raposo; M. Hernandez |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-642-2125 | Medium | ||
| Area | Expedition | Conference | IbPRIA | ||
| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ VSR2011 | Serial | 1730 | ||
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| Author | Maria Vanrell; Naila Murray; Robert Benavente; C. Alejandro Parraga; Xavier Otazu; Ramon Baldrich | ||||
| Title |
Perception Based Representations for Computational Colour | Type | Conference Article | ||
| Year | 2011 | Publication | 3rd International Workshop on Computational Color Imaging | Abbreviated Journal | |
| Volume | 6626 | Issue | Pages | 16-30 | |
| Keywords | colour perception, induction, naming, psychophysical data, saliency, segmentation | ||||
| Abstract | The perceived colour of a stimulus is dependent on multiple factors stemming out either from the context of the stimulus or idiosyncrasies of the observer. The complexity involved in combining these multiple effects is the main reason for the gap between classical calibrated colour spaces from colour science and colour representations used in computer vision, where colour is just one more visual cue immersed in a digital image where surfaces, shadows and illuminants interact seemingly out of control. With the aim to advance a few steps towards bridging this gap we present some results on computational representations of colour for computer vision. They have been developed by introducing perceptual considerations derived from the interaction of the colour of a point with its context. We show some techniques to represent the colour of a point influenced by assimilation and contrast effects due to the image surround and we show some results on how colour saliency can be derived in real images. We outline a model for automatic assignment of colour names to image points directly trained on psychophysical data. We show how colour segments can be perceptually grouped in the image by imposing shading coherence in the colour space. | ||||
| Address | Milan, Italy | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer-Verlag | Place of Publication | Editor | Raimondo Schettini, Shoji Tominaga, Alain Trémeau | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-642-20403-6 | Medium | ||
| Area | Expedition | Conference | CCIW | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ VMB2011 | Serial | 1733 | ||
| Permanent link to this record | |||||
| Author | Jaime Moreno | ||||
| Title |
Perceptual Criteria on Image Compresions | Type | Book Whole | ||
| Year | 2011 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
| Volume | Issue | Pages | |||
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| Abstract | Nowadays, digital images are used in many areas in everyday life, but they tend to be big. This increases amount of information leads us to the problem of image data storage. For example, it is common to have a representation a color pixel as a 24-bit number, where the channels red, green, and blue employ 8 bits each. In consequence, this kind of color pixel can specify one of 224 ¼ 16:78 million colors. Therefore, an image at a resolution of 512 £ 512 that allocates 24 bits per pixel, occupies 786,432 bytes. That is why image compression is important. An important feature of image compression is that it can be lossy or lossless. A compressed image is acceptable provided these losses of image information are not perceived by the eye. It is possible to assume that a portion of this information is redundant. Lossless Image Compression is defined as to mathematically decode the same image which was encoded. In Lossy Image Compression needs to identify two features inside the image: the redundancy and the irrelevancy of information. Thus, lossy compression modifies the image data in such a way when they are encoded and decoded, the recovered image is similar enough to the original one. How similar is the recovered image in comparison to the original image is defined prior to the compression process, and it depends on the implementation to be performed. In lossy compression, current image compression schemes remove information considered irrelevant by using mathematical criteria. One of the problems of these schemes is that although the numerical quality of the compressed image is low, it shows a high visual image quality, e.g. it does not show a lot of visible artifacts. It is because these mathematical criteria, used to remove information, do not take into account if the viewed information is perceived by the Human Visual System. Therefore, the aim of an image compression scheme designed to obtain images that do not show artifacts although their numerical quality can be low, is to eliminate the information that is not visible by the Human Visual System. Hence, this Ph.D. thesis proposes to exploit the visual redundancy existing in an image by reducing those features that can be unperceivable for the Human Visual System. First, we define an image quality assessment, which is highly correlated with the psychophysical experiments performed by human observers. The proposed CwPSNR metrics weights the well-known PSNR by using a particular perceptual low level model of the Human Visual System, e.g. the Chromatic Induction Wavelet Model (CIWaM). Second, we propose an image compression algorithm (called Hi-SET), which exploits the high correlation and self-similarity of pixels in a given area or neighborhood by means of a fractal function. Hi-SET possesses the main features that modern image compressors have, that is, it is an embedded coder, which allows a progressive transmission. Third, we propose a perceptual quantizer (½SQ), which is a modification of the uniform scalar quantizer. The ½SQ is applied to a pixel set in a certain Wavelet sub-band, that is, a global quantization. Unlike this, the proposed modification allows to perform a local pixel-by-pixel forward and inverse quantization, introducing into this process a perceptual distortion which depends on the surround spatial information of the pixel. Combining ½SQ method with the Hi-SET image compressor, we define a perceptual image compressor, called ©SET. Finally, a coding method for Region of Interest areas is presented, ½GBbBShift, which perceptually weights pixels into these areas and maintains only the more important perceivable features in the rest of the image. Results presented in this report show that CwPSNR is the best-ranked image quality method when it is applied to the most common image compression distortions such as JPEG and JPEG2000. CwPSNR shows the best correlation with the judgement of human observers, which is based on the results of psychophysical experiments obtained for relevant image quality databases such as TID2008, LIVE, CSIQ and IVC. Furthermore, Hi-SET coder obtains better results both for compression ratios and perceptual image quality than the JPEG2000 coder and other coders that use a Hilbert Fractal for image compression. Hence, when the proposed perceptual quantization is introduced to Hi-SET coder, our compressor improves its numerical and perceptual e±ciency. When ½GBbBShift method applied to Hi-SET is compared against MaxShift method applied to the JPEG2000 standard and Hi-SET, the images coded by our ROI method get the best results when the overall image quality is estimated. Both the proposed perceptual quantization and the ½GBbBShift method are generalized algorithms that can be applied to other Wavelet based image compression algorithms such as JPEG2000, SPIHT or SPECK. | ||||
| Address | |||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Xavier Otazu | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-84-938351-3-2 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ Mor2011 | Serial | 1786 | ||
| Permanent link to this record | |||||
| Author | Simone Balocco; Carlo Gatta; Xavier Carrillo; J. Mauri; Petia Radeva | ||||
| Title |
Plaque Type, Plaque Burden and Wall Shear Stress Relation in Coronary Arteries Assessed by X-ray Angiography and Intravascular Ultrasound: a Qualitative Study | Type | Conference Article | ||
| Year | 2011 | Publication | 14th International Symposium on Applied Sciences in Biomedical and Communication Technologies | Abbreviated Journal | |
| Volume | Issue | Pages | |||
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| Abstract | In this paper, we present a complete framework that automatically provides fluid-dynamic and plaque analysis from IVUS and Angiographic sequences. Such framework is used to analyze, in three coronary arteries, the relation between wall shear stress with type and amount of plaque. Preliminary qualitative results show an inverse relation between the wall shear stress and the plaque burden, which is confirmed by the fact that the plaque growth is higher on the wall having concave curvature. Regarding the plaque type it was observed that regions having low shear stress are predominantly fibro-lipidic while the heavy calcifications are in general located in areas of the vessel having high WSS. | ||||
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| ISSN | ISBN | 978-1-4503-0913-4 | Medium | ||
| Area | Expedition | Conference | ISABEL | ||
| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @ BGC2011b | Serial | 1799 | ||
| Permanent link to this record | |||||
| Author | Fahad Shahbaz Khan; Joost Van de Weijer; Andrew Bagdanov; Maria Vanrell | ||||
| Title |
Portmanteau Vocabularies for Multi-Cue Image Representation | Type | Conference Article | ||
| Year | 2011 | Publication | 25th Annual Conference on Neural Information Processing Systems | Abbreviated Journal | |
| Volume | Issue | Pages | |||
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| Abstract | We describe a novel technique for feature combination in the bag-of-words model of image classification. Our approach builds discriminative compound words from primitive cues learned independently from training images. Our main observation is that modeling joint-cue distributions independently is more statistically robust for typical classification problems than attempting to empirically estimate the dependent, joint-cue distribution directly. We use Information theoretic vocabulary compression to find discriminative combinations of cues and the resulting vocabulary of portmanteau words is compact, has the cue binding property, and supports individual weighting of cues in the final image representation. State-of-the-art results on both the Oxford Flower-102 and Caltech-UCSD Bird-200 datasets demonstrate the effectiveness of our technique compared to other, significantly more complex approaches to multi-cue image representation | ||||
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| Language | Summary Language | Original Title | |||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | NIPS | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ KWB2011 | Serial | 1865 | ||
| Permanent link to this record | |||||
| Author | Mario Rojas; David Masip; Jordi Vitria | ||||
| Title |
Predicting Dominance Judgements Automatically: A Machine Learning Approach. | Type | Conference Article | ||
| Year | 2011 | Publication | IEEE International Workshop on Social Behavior Analysis | Abbreviated Journal | |
| Volume | Issue | Pages | 939-944 | ||
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| Abstract | The amount of multimodal devices that surround us is growing everyday. In this context, human interaction and communication have become a focus of attention and a hot topic of research. A crucial element in human relations is the evaluation of individuals with respect to facial traits, what is called a first impression. Studies based on appearance have suggested that personality can be expressed by appearance and the observer may use such information to form judgments. In the context of rapid facial evaluation, certain personality traits seem to have a more pronounced effect on the relations and perceptions inside groups. The perception of dominance has been shown to be an active part of social roles at different stages of life, and even play a part in mate selection. The aim of this paper is to study to what extent this information is learnable from the point of view of computer science. Specifically we intend to determine if judgments of dominance can be learned by machine learning techniques. We implement two different descriptors in order to assess this. The first is the histogram of oriented gradients (HOG), and the second is a probabilistic appearance descriptor based on the frequencies of grouped binary tests. State of the art classification rules validate the performance of both descriptors, with respect to the prediction task. Experimental results show that machine learning techniques can predict judgments of dominance rather accurately (accuracies up to 90%) and that the HOG descriptor may characterize appropriately the information necessary for such task. | ||||
| Address | Santa Barbara, CA | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-4244-9140-7 | Medium | ||
| Area | Expedition | Conference | SBA | ||
| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ RMV2011b | Serial | 1760 | ||
| Permanent link to this record | |||||
| Author | Ferran Diego | ||||
| Title |
Probabilistic Alignment of Video Sequences Recorded by Moving Cameras | Type | Book Whole | ||
| Year | 2011 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
| Volume | Issue | Pages | |||
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| Abstract | Video alignment consists of integrating multiple video sequences recorded independently into a single video sequence. This means to register both in time (synchronize
frames) and space (image registration) so that the two videos sequences can be fused or compared pixel–wise. In spite of being relatively unknown, many applications today may benefit from the availability of robust and efficient video alignment methods. For instance, video surveillance requires to integrate video sequences that are recorded of the same scene at different times in order to detect changes. The problem of aligning videos has been addressed before, but in the relatively simple cases of fixed or rigidly attached cameras and simultaneous acquisition. In addition, most works rely on restrictive assumptions which reduce its difficulty such as linear time correspondence or the knowledge of the complete trajectories of corresponding scene points on the images; to some extent, these assumptions limit the practical applicability of the solutions developed until now. In this thesis, we focus on the challenging problem of aligning sequences recorded at different times from independent moving cameras following similar but not coincident trajectories. More precisely, this thesis covers four studies that advance the state-of-the-art in video alignment. First, we focus on analyzing and developing a probabilistic framework for video alignment, that is, a principled way to integrate multiple observations and prior information. In this way, two different approaches are presented to exploit the combination of several purely visual features (image–intensities, visual words and dense motion field descriptor), and global positioning system (GPS) information. Second, we focus on reformulating the problem into a single alignment framework since previous works on video alignment adopt a divide–and–conquer strategy, i.e., first solve the synchronization, and then register corresponding frames. This also generalizes the ’classic’ case of fixed geometric transform and linear time mapping. Third, we focus on exploiting directly the time domain of the video sequences in order to avoid exhaustive cross–frame search. This provides relevant information used for learning the temporal mapping between pairs of video sequences. Finally, we focus on adapting these methods to the on–line setting for road detection and vehicle geolocation. The qualitative and quantitative results presented in this thesis on a variety of real–world pairs of video sequences show that the proposed method is: robust to varying imaging conditions, different image content (e.g., incoming and outgoing vehicles), variations on camera velocity, and different scenarios (indoor and outdoor) going beyond the state–of–the–art. Moreover, the on–line video alignment has been successfully applied for road detection and vehicle geolocation achieving promising results. |
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| Address | |||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Joan Serrat | |
| Language | Summary Language | Original Title | |||
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| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ Die2011 | Serial | 1787 | ||
| Permanent link to this record | |||||
| Author | Mirko Arnold; Stephan Ameling; Anarta Ghosh; Gerard Lacey | ||||
| Title |
Quality Improvement of Endoscopy Videos | Type | Conference Article | ||
| Year | 2011 | Publication | Proceedings of the 8th IASTED International Conference on Biomedical Engineering | Abbreviated Journal | |
| Volume | 723 | Issue | Pages | ||
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| ISSN | ISBN | Medium | |||
| Area | 800 | Expedition | Conference | ||
| Notes | MV | Approved | no | ||
| Call Number | fernando @ fernando @ | Serial | 2426 | ||
| Permanent link to this record | |||||
| Author | Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez | ||||
| Title |
Rank Estimation in Missing Data Matrix Problems | Type | Journal Article | ||
| Year | 2011 | Publication | Journal of Mathematical Imaging and Vision | Abbreviated Journal | JMIV |
| Volume | 39 | Issue | 2 | Pages | 140-160 |
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| Abstract | A novel technique for missing data matrix rank estimation is presented. It is focused on matrices of trajectories, where every element of the matrix corresponds to an image coordinate from a feature point of a rigid moving object at a given frame; missing data are represented as empty entries. The objective of the proposed approach is to estimate the rank of a missing data matrix in order to fill in empty entries with some matrix completion method, without using or assuming neither the number of objects contained in the scene nor the kind of their motion. The key point of the proposed technique consists in studying the frequency behaviour of the individual trajectories, which are seen as 1D signals. The main assumption is that due to the rigidity of the moving objects, the frequency content of the trajectories will be similar after filling in their missing entries. The proposed rank estimation approach can be used in different computer vision problems, where the rank of a missing data matrix needs to be estimated. Experimental results with synthetic and real data are provided in order to empirically show the good performance of the proposed approach. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0924-9907 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ JSL2011; | Serial | 1710 | ||
| Permanent link to this record | |||||
| Author | Jose Seabra; Francesco Ciompi; Oriol Pujol; J. Mauri; Petia Radeva; Joao Sanchez | ||||
| Title |
Rayleigh Mixture Model for Plaque Characterization in Intravascular Ultrasound | Type | Journal Article | ||
| Year | 2011 | Publication | IEEE Transactions on Biomedical Engineering | Abbreviated Journal | TBME |
| Volume | 58 | Issue | 5 | Pages | 1314-1324 |
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| Abstract | Vulnerable plaques are the major cause of carotid and coronary vascular problems, such as heart attack or stroke. A correct modeling of plaque echomorphology and composition can help the identification of such lesions. The Rayleigh distribution is widely used to describe (nearly) homogeneous areas in ultrasound images. Since plaques may contain tissues with heterogeneous regions, more complex distributions depending on multiple parameters are usually needed, such as Rice, K or Nakagami distributions. In such cases, the problem formulation becomes more complex, and the optimization procedure to estimate the plaque echomorphology is more difficult. Here, we propose to model the tissue echomorphology by means of a mixture of Rayleigh distributions, known as the Rayleigh mixture model (RMM). The problem formulation is still simple, but its ability to describe complex textural patterns is very powerful. In this paper, we present a method for the automatic estimation of the RMM mixture parameters by means of the expectation maximization algorithm, which aims at characterizing tissue echomorphology in ultrasound (US). The performance of the proposed model is evaluated with a database of in vitro intravascular US cases. We show that the mixture coefficients and Rayleigh parameters explicitly derived from the mixture model are able to accurately describe different plaque types and to significantly improve the characterization performance of an already existing methodology. | ||||
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| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ SCP2011 | Serial | 1712 | ||
| Permanent link to this record | |||||
| Author | C. Alejandro Parraga; Olivier Penacchio; Maria Vanrell | ||||
| Title |
Retinal Filtering Matches Natural Image Statistics at Low Luminance Levels | Type | Journal Article | ||
| Year | 2011 | Publication | Perception | Abbreviated Journal | PER |
| Volume | 40 | Issue | Pages | 96 | |
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| Abstract | The assumption that the retina’s main objective is to provide a minimum entropy representation to higher visual areas (ie efficient coding principle) allows to predict retinal filtering in space–time and colour (Atick, 1992 Network 3 213–251). This is achieved by considering the power spectra of natural images (which is proportional to 1/f2) and the suppression of retinal and image noise. However, most studies consider images within a limited range of lighting conditions (eg near noon) whereas the visual system’s spatial filtering depends on light intensity and the spatiochromatic properties of natural scenes depend of the time of the day. Here, we explore whether the dependence of visual spatial filtering on luminance match the changes in power spectrum of natural scenes at different times of the day. Using human cone-activation based naturalistic stimuli (from the Barcelona Calibrated Images Database), we show that for a range of luminance levels, the shape of the retinal CSF reflects the slope of the power spectrum at low spatial frequencies. Accordingly, the retina implements the filtering which best decorrelates the input signal at every luminance level. This result is in line with the body of work that places efficient coding as a guiding neural principle. | ||||
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| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ PPV2011 | Serial | 1720 | ||
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| Author | Jose Manuel Alvarez; Antonio Lopez | ||||
| Title |
Road Detection Based on Illuminant Invariance | Type | Journal Article | ||
| Year | 2011 | Publication | IEEE Transactions on Intelligent Transportation Systems | Abbreviated Journal | TITS |
| Volume | 12 | Issue | 1 | Pages | 184-193 |
| Keywords | road detection | ||||
| Abstract | By using an onboard camera, it is possible to detect the free road surface ahead of the ego-vehicle. Road detection is of high relevance for autonomous driving, road departure warning, and supporting driver-assistance systems such as vehicle and pedestrian detection. The key for vision-based road detection is the ability to classify image pixels as belonging or not to the road surface. Identifying road pixels is a major challenge due to the intraclass variability caused by lighting conditions. A particularly difficult scenario appears when the road surface has both shadowed and nonshadowed areas. Accordingly, we propose a novel approach to vision-based road detection that is robust to shadows. The novelty of our approach relies on using a shadow-invariant feature space combined with a model-based classifier. The model is built online to improve the adaptability of the algorithm to the current lighting and the presence of other vehicles in the scene. The proposed algorithm works in still images and does not depend on either road shape or temporal restrictions. Quantitative and qualitative experiments on real-world road sequences with heavy traffic and shadows show that the method is robust to shadows and lighting variations. Moreover, the proposed method provides the highest performance when compared with hue-saturation-intensity (HSI)-based algorithms. | ||||
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| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ AlL2011 | Serial | 1456 | ||
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| Author | Naila Murray; Maria Vanrell; Xavier Otazu; C. Alejandro Parraga | ||||
| Title |
Saliency Estimation Using a Non-Parametric Low-Level Vision Model | Type | Conference Article | ||
| Year | 2011 | Publication | IEEE conference on Computer Vision and Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 433-440 | ||
| Keywords | Gaussian mixture model;ad hoc parameter selection;center-surround inhibition windows;center-surround mechanism;color appearance model;convolution;eye-fixation data;human vision;innate spatial pooling mechanism;inverse wavelet transform;low-level visual front-end;nonparametric low-level vision model;saliency estimation;saliency map;scale integration;scale-weighted center-surround response;scale-weighting function;visual task;Gaussian processes;biology;biology computing;colour vision;computer vision;visual perception;wavelet transforms | ||||
| Abstract | Many successful models for predicting attention in a scene involve three main steps: convolution with a set of filters, a center-surround mechanism and spatial pooling to construct a saliency map. However, integrating spatial information and justifying the choice of various parameter values remain open problems. In this paper we show that an efficient model of color appearance in human vision, which contains a principled selection of parameters as well as an innate spatial pooling mechanism, can be generalized to obtain a saliency model that outperforms state-of-the-art models. Scale integration is achieved by an inverse wavelet transform over the set of scale-weighted center-surround responses. The scale-weighting function (termed ECSF) has been optimized to better replicate psychophysical data on color appearance, and the appropriate sizes of the center-surround inhibition windows have been determined by training a Gaussian Mixture Model on eye-fixation data, thus avoiding ad-hoc parameter selection. Additionally, we conclude that the extension of a color appearance model to saliency estimation adds to the evidence for a common low-level visual front-end for different visual tasks. | ||||
| Address | Colorado Springs | ||||
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| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1063-6919 | ISBN | 978-1-4577-0394-2 | Medium | |
| Area | Expedition | Conference | CVPR | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ MVO2011 | Serial | 1757 | ||
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| Author | Koen E.A. van de Sande; Jasper Uilings; Theo Gevers; Arnold Smeulders | ||||
| Title |
Segmentation as Selective Search for Object Recognition | Type | Conference Article | ||
| Year | 2011 | Publication | 13th IEEE International Conference on Computer Vision | Abbreviated Journal | |
| Volume | Issue | Pages | 1879-1886 | ||
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| Abstract | For object recognition, the current state-of-the-art is based on exhaustive search. However, to enable the use of more expensive features and classifiers and thereby progress beyond the state-of-the-art, a selective search strategy is needed. Therefore, we adapt segmentation as a selective search by reconsidering segmentation: We propose to generate many approximate locations over few and precise object delineations because (1) an object whose location is never generated can not be recognised and (2) appearance and immediate nearby context are most effective for object recognition. Our method is class-independent and is shown to cover 96.7% of all objects in the Pascal VOC 2007 test set using only 1,536 locations per image. Our selective search enables the use of the more expensive bag-of-words method which we use to substantially improve the state-of-the-art by up to 8.5% for 8 out of 20 classes on the Pascal VOC 2010 detection challenge. | ||||
| Address | Barcelona | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1550-5499 | ISBN | 978-1-4577-1101-5 | Medium | |
| Area | Expedition | Conference | ICCV | ||
| Notes | ISE | Approved | no | ||
| Call Number | Admin @ si @ SUG2011 | Serial | 1780 | ||
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| Author | Nataliya Shapovalova; Carles Fernandez; Xavier Roca; Jordi Gonzalez | ||||
| Title |
Semantics of Human Behavior in Image Sequences | Type | Book Chapter | ||
| Year | 2011 | Publication | Computer Analysis of Human Behavior | Abbreviated Journal | |
| Volume | Issue | 7 | Pages | 151-182 | |
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| Abstract | Human behavior is contextualized and understanding the scene of an action is crucial for giving proper semantics to behavior. In this chapter we present a novel approach for scene understanding. The emphasis of this work is on the particular case of Human Event Understanding. We introduce a new taxonomy to organize the different semantic levels of the Human Event Understanding framework proposed. Such a framework particularly contributes to the scene understanding domain by (i) extracting behavioral patterns from the integrative analysis of spatial, temporal, and contextual evidence and (ii) integrative analysis of bottom-up and top-down approaches in Human Event Understanding. We will explore how the information about interactions between humans and their environment influences the performance of activity recognition, and how this can be extrapolated to the temporal domain in order to extract higher inferences from human events observed in sequences of images. | ||||
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| Publisher | Springer London | Place of Publication | Editor | Albert Ali Salah; | |
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-0-85729-993-2 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ISE | Approved | no | ||
| Call Number | Admin @ si @ SFR2011 | Serial | 1810 | ||
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