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Joan Mas; Josep Llados; Gemma Sanchez; J.A. Jorge |
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Title |
A syntactic approach based on distortion-tolerant Adjacency Grammars and a spatial-directed parser to interpret sketched diagrams |
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Journal Article |
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Year |
2010 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
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Volume |
43 |
Issue |
12 |
Pages |
4148–4164 |
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Keywords  |
Syntactic Pattern Recognition; Symbol recognition; Diagram understanding; Sketched diagrams; Adjacency Grammars; Incremental parsing; Spatial directed parsing |
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Abstract |
This paper presents a syntactic approach based on Adjacency Grammars (AG) for sketch diagram modeling and understanding. Diagrams are a combination of graphical symbols arranged according to a set of spatial rules defined by a visual language. AG describe visual shapes by productions defined in terms of terminal and non-terminal symbols (graphical primitives and subshapes), and a set functions describing the spatial arrangements between symbols. Our approach to sketch diagram understanding provides three main contributions. First, since AG are linear grammars, there is a need to define shapes and relations inherently bidimensional using a sequential formalism. Second, our parsing approach uses an indexing structure based on a spatial tessellation. This serves to reduce the search space when finding candidates to produce a valid reduction. This allows order-free parsing of 2D visual sentences while keeping combinatorial explosion in check. Third, working with sketches requires a distortion model to cope with the natural variations of hand drawn strokes. To this end we extended the basic grammar with a distortion measure modeled on the allowable variation on spatial constraints associated with grammar productions. Finally, the paper reports on an experimental framework an interactive system for sketch analysis. User tests performed on two real scenarios show that our approach is usable in interactive settings. |
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Elsevier |
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no |
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DAG @ dag @ MLS2010 |
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1336 |
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Author |
Ferran Diego; Daniel Ponsa; Joan Serrat; Antonio Lopez |
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Title |
Vehicle geolocalization based on video synchronization |
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Conference Article |
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Year |
2010 |
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13th Annual International Conference on Intelligent Transportation Systems |
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1511–1516 |
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Keywords |
video alignment |
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Abstract |
TC8.6
This paper proposes a novel method for estimating the geospatial localization of a vehicle. I uses as input a georeferenced video sequence recorded by a forward-facing camera attached to the windscreen. The core of the proposed method is an on-line video synchronization which finds out the corresponding frame in the georeferenced video sequence to the one recorded at each time by the camera on a second drive through the same track. Once found the corresponding frame in the georeferenced video sequence, we transfer its geospatial information of this frame. The key advantages of this method are: 1) the increase of the update rate and the geospatial accuracy with regard to a standard low-cost GPS and 2) the ability to localize a vehicle even when a GPS is not available or is not reliable enough, like in certain urban areas. Experimental results for an urban environments are presented, showing an average of relative accuracy of 1.5 meters. |
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Madeira Island (Portugal) |
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2153-0009 |
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978-1-4244-7657-2 |
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ITSC |
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ADAS |
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ADAS @ adas @ DPS2010 |
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1423 |
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Author |
Ferran Diego; Jose Manuel Alvarez; Joan Serrat; Antonio Lopez |
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Title |
Vision-based road detection via on-line video registration |
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Conference Article |
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2010 |
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13th Annual International Conference on Intelligent Transportation Systems |
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1135–1140 |
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video alignment; road detection |
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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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Madeira Island (Portugal) |
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2153-0009 |
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978-1-4244-7657-2 |
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ITSC |
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ADAS |
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ADAS @ adas @ DAS2010 |
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1424 |
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Author |
Xavier Otazu; C. Alejandro Parraga; Maria Vanrell |
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Title |
Towards a unified chromatic inducction model |
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Journal Article |
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Year |
2010 |
Publication |
Journal of Vision |
Abbreviated Journal |
VSS |
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10 |
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12:5 |
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1-24 |
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Visual system; Color induction; Wavelet transform |
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In a previous work (X. Otazu, M. Vanrell, & C. A. Párraga, 2008b), we showed how several brightness induction effects can be predicted using a simple multiresolution wavelet model (BIWaM). Here we present a new model for chromatic induction processes (termed Chromatic Induction Wavelet Model or CIWaM), which is also implemented on a multiresolution framework and based on similar assumptions related to the spatial frequency and the contrast surround energy of the stimulus. The CIWaM can be interpreted as a very simple extension of the BIWaM to the chromatic channels, which in our case are defined in the MacLeod-Boynton (lsY) color space. This new model allows us to unify both chromatic assimilation and chromatic contrast effects in a single mathematical formulation. The predictions of the CIWaM were tested by means of several color and brightness induction experiments, which showed an acceptable agreement between model predictions and psychophysical data. |
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CIC |
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CAT @ cat @ OPV2010 |
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1450 |
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Author |
Jose Antonio Rodriguez; Florent Perronnin; Gemma Sanchez; Josep Llados |
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Title |
Unsupervised writer adaptation of whole-word HMMs with application to word-spotting |
Type |
Journal Article |
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Year |
2010 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
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Volume |
31 |
Issue |
8 |
Pages |
742–749 |
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Keywords |
Word-spotting; Handwriting recognition; Writer adaptation; Hidden Markov model; Document analysis |
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In this paper we propose a novel approach for writer adaptation in a handwritten word-spotting task. The method exploits the fact that the semi-continuous hidden Markov model separates the word model parameters into (i) a codebook of shapes and (ii) a set of word-specific parameters.
Our main contribution is to employ this property to derive writer-specific word models by statistically adapting an initial universal codebook to each document. This process is unsupervised and does not even require the appearance of the keyword(s) in the searched document. Experimental results show an increase in performance when this adaptation technique is applied. To the best of our knowledge, this is the first work dealing with adaptation for word-spotting. The preliminary version of this paper obtained an IBM Best Student Paper Award at the 19th International Conference on Pattern Recognition. |
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Elsevier |
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DAG @ dag @ RPS2010 |
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1290 |
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