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| Author | Mariella Dimiccoli | ||||
| Title | Figure-ground segregation: A fully nonlocal approach | Type | Journal Article | ||
| Year | 2016 | Publication | Vision Research | Abbreviated Journal | VR |
| Volume | 126 | Issue  |
Pages | 308-317 | |
| Keywords | Figure-ground segregation; Nonlocal approach; Directional linear voting; Nonlinear diffusion | ||||
| Abstract | We present a computational model that computes and integrates in a nonlocal fashion several configural cues for automatic figure-ground segregation. Our working hypothesis is that the figural status of each pixel is a nonlocal function of several geometric shape properties and it can be estimated without explicitly relying on object boundaries. The methodology is grounded on two elements: multi-directional linear voting and nonlinear diffusion. A first estimation of the figural status of each pixel is obtained as a result of a voting process, in which several differently oriented line-shaped neighborhoods vote to express their belief about the figural status of the pixel. A nonlinear diffusion process is then applied to enforce the coherence of figural status estimates among perceptually homogeneous regions. Computer simulations fit human perception and match the experimental evidence that several cues cooperate in defining figure-ground segregation. The results of this work suggest that figure-ground segregation involves feedback from cells with larger receptive fields in higher visual cortical areas. | ||||
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| Notes | MILAB; | Approved | no | ||
| Call Number | Admin @ si @ Dim2016b | Serial | 2623 | ||
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| Author | L. Calvet; A. Ferrer; M. Gomes; A. Juan; David Masip | ||||
| Title | Combining Statistical Learning with Metaheuristics for the Multi-Depot Vehicle Routing Problem with Market Segmentation | Type | Journal Article | ||
| Year | 2016 | Publication | Computers & Industrial Engineering | Abbreviated Journal | CIE |
| Volume | 94 | Issue |
Pages | 93-104 | |
| Keywords | Multi-Depot Vehicle Routing Problem; market segmentation applications; hybrid algorithms; statistical learning | ||||
| Abstract | In real-life logistics and distribution activities it is usual to face situations in which the distribution of goods has to be made from multiple warehouses or depots to the nal customers. This problem is known as the Multi-Depot Vehicle Routing Problem (MDVRP), and it typically includes two sequential and correlated stages: (a) the assignment map of customers to depots, and (b) the corresponding design of the distribution routes. Most of the existing work in the literature has focused on minimizing distance-based distribution costs while satisfying a number of capacity constraints. However, no attention has been given so far to potential variations in demands due to the tness of the customerdepot mapping in the case of heterogeneous depots. In this paper, we consider this realistic version of the problem in which the depots are heterogeneous in terms of their commercial o er and customers show di erent willingness to consume depending on how well the assigned depot ts their preferences. Thus, we assume that di erent customer-depot assignment maps will lead to di erent customer-expenditure levels. As a consequence, market-segmentation strategiesneed to be considered in order to increase sales and total income while accounting for the distribution costs. To solve this extension of the MDVRP, we propose a hybrid approach that combines statistical learning techniques with a metaheuristic framework. First, a set of predictive models is generated from historical data. These statistical models allow estimating the demand of any customer depending on the assigned depot. Then, the estimated expenditure of each customer is included as part of an enriched objective function as a way to better guide the stochastic local search inside the metaheuristic framework. A set of computational experiments contribute to illustrate our approach and how the extended MDVRP considered here di ers in terms of the proposed solutions from the traditional one. | ||||
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| Publisher | PERGAMON-ELSEVIER SCIENCE LTD | Place of Publication | Editor | ||
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| Series Editor | Series Title | Abbreviated Series Title | CIE | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0360-8352 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | OR;MV; | Approved | no | ||
| Call Number | Admin @ si @ CFG2016 | Serial | 2749 | ||
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| Author | Jiaolong Xu; David Vazquez; Krystian Mikolajczyk; Antonio Lopez | ||||
| Title | Hierarchical online domain adaptation of deformable part-based models | Type | Conference Article | ||
| Year | 2016 | Publication | IEEE International Conference on Robotics and Automation | Abbreviated Journal | |
| Volume | Issue |
Pages | 5536-5541 | ||
| Keywords | Domain Adaptation; Pedestrian Detection | ||||
| Abstract | We propose an online domain adaptation method for the deformable part-based model (DPM). The online domain adaptation is based on a two-level hierarchical adaptation tree, which consists of instance detectors in the leaf nodes and a category detector at the root node. Moreover, combined with a multiple object tracking procedure (MOT), our proposal neither requires target-domain annotated data nor revisiting the source-domain data for performing the source-to-target domain adaptation of the DPM. From a practical point of view this means that, given a source-domain DPM and new video for training on a new domain without object annotations, our procedure outputs a new DPM adapted to the domain represented by the video. As proof-of-concept we apply our proposal to the challenging task of pedestrian detection. In this case, each instance detector is an exemplar classifier trained online with only one pedestrian per frame. The pedestrian instances are collected by MOT and the hierarchical model is constructed dynamically according to the pedestrian trajectories. Our experimental results show that the adapted detector achieves the accuracy of recent supervised domain adaptation methods (i.e., requiring manually annotated targetdomain data), and improves the source detector more than 10 percentage points. | ||||
| Address | Stockholm; Sweden; May 2016 | ||||
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| Area | Expedition | Conference | ICRA | ||
| Notes | ADAS; 600.085; 600.082; 600.076 | Approved | no | ||
| Call Number | Admin @ si @ XVM2016 | Serial | 2728 | ||
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| Author | Carlos David Martinez Hinarejos; Josep Llados; Alicia Fornes; Francisco Casacuberta; Lluis de Las Heras; Joan Mas; Moises Pastor; Oriol Ramos Terrades; Joan Andreu Sanchez; Enrique Vidal; Fernando Vilariño | ||||
| Title | Context, multimodality, and user collaboration in handwritten text processing: the CoMUN-HaT project | Type | Conference Article | ||
| Year | 2016 | Publication | 3rd IberSPEECH | Abbreviated Journal | |
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| Abstract | Processing of handwritten documents is a task that is of wide interest for many
purposes, such as those related to preserve cultural heritage. Handwritten text recognition techniques have been successfully applied during the last decade to obtain transcriptions of handwritten documents, and keyword spotting techniques have been applied for searching specific terms in image collections of handwritten documents. However, results on transcription and indexing are far from perfect. In this framework, the use of new data sources arises as a new paradigm that will allow for a better transcription and indexing of handwritten documents. Three main different data sources could be considered: context of the document (style, writer, historical time, topics,. . . ), multimodal data (representations of the document in a different modality, such as the speech signal of the dictation of the text), and user feedback (corrections, amendments,. . . ). The CoMUN-HaT project aims at the integration of these different data sources into the transcription and indexing task for handwritten documents: the use of context derived from the analysis of the documents, how multimodality can aid the recognition process to obtain more accurate transcriptions (including transcription in a modern version of the language), and integration into a userin-the-loop assisted text transcription framework. This will be reflected in the construction of a transcription and indexing platform that can be used by both professional and nonprofessional users, contributing to crowd-sourcing activities to preserve cultural heritage and to obtain an accessible version of the involved corpus. |
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| Address | Lisboa; Portugal; November 2016 | ||||
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| Area | Expedition | Conference | IberSPEECH | ||
| Notes | DAG; MV; 600.097;SIAI | Approved | no | ||
| Call Number | Admin @ si @MLF2016 | Serial | 2813 | ||
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| Author | Mariella Dimiccoli; Jean-Pascal Jacob; Lionel Moisan | ||||
| Title | Particle detection and tracking in fluorescence time-lapse imaging: a contrario approach | Type | Journal Article | ||
| Year | 2016 | Publication | Journal of Machine Vision and Applications | Abbreviated Journal | MVAP |
| Volume | 27 | Issue |
Pages | 511-527 | |
| Keywords | particle detection; particle tracking; a-contrario approach; time-lapse fluorescence imaging | ||||
| Abstract | In this work, we propose a probabilistic approach for the detection and the
tracking of particles on biological images. In presence of very noised and poor quality data, particles and trajectories can be characterized by an a-contrario model, that estimates the probability of observing the structures of interest in random data. This approach, first introduced in the modeling of human visual perception and then successfully applied in many image processing tasks, leads to algorithms that do not require a previous learning stage, nor a tedious parameter tuning and are very robust to noise. Comparative evaluations against a well established baseline show that the proposed approach outperforms the state of the art. |
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| Notes | MILAB; | Approved | no | ||
| Call Number | Admin @ si @ DJM2016 | Serial | 2735 | ||
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| Author | Victor Campmany; Sergio Silva; Juan Carlos Moure; Toni Espinosa; David Vazquez; Antonio Lopez | ||||
| Title | GPU-based pedestrian detection for autonomous driving | Type | Conference Article | ||
| Year | 2016 | Publication | GPU Technology Conference | Abbreviated Journal | |
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| Keywords | Pedestrian Detection; GPU | ||||
| Abstract | Pedestrian detection for autonomous driving is one of the hardest tasks within computer vision, and involves huge computational costs. Obtaining acceptable real-time performance, measured in frames per second (fps), for the most advanced algorithms is nowadays a hard challenge. Taking the work in [1] as our baseline, we propose a CUDA implementation of a pedestrian detection system that includes LBP and HOG as feature descriptors and SVM and Random forest as classifiers. We introduce significant algorithmic adjustments and optimizations to adapt the problem to the NVIDIA GPU architecture. The aim is to deploy a real-time system providing reliable results. | ||||
| Address | Silicon Valley; San Francisco; USA; April 2016 | ||||
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| Area | Expedition | Conference | GTC | ||
| Notes | ADAS; 600.085; 600.082; 600.076 | Approved | no | ||
| Call Number | ADAS @ adas @ CSM2016 | Serial | 2737 | ||
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| Author | Daniel Hernandez; Juan Carlos Moure; Toni Espinosa; Alejandro Chacon; David Vazquez; Antonio Lopez | ||||
| Title | Real-time 3D Reconstruction for Autonomous Driving via Semi-Global Matching | Type | Conference Article | ||
| Year | 2016 | Publication | GPU Technology Conference | Abbreviated Journal | |
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| Keywords | Stereo; Autonomous Driving; GPU; 3d reconstruction | ||||
| Abstract | Robust and dense computation of depth information from stereo-camera systems is a computationally demanding requirement for real-time autonomous driving. Semi-Global Matching (SGM) [1] approximates heavy-computation global algorithms results but with lower computational complexity, therefore it is a good candidate for a real-time implementation. SGM minimizes energy along several 1D paths across the image. The aim of this work is to provide a real-time system producing reliable results on energy-efficient hardware. Our design runs on a NVIDIA Titan X GPU at 104.62 FPS and on a NVIDIA Drive PX at 6.7 FPS, promising for real-time platforms | ||||
| Address | Silicon Valley; San Francisco; USA; April 2016 | ||||
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| Area | Expedition | Conference | GTC | ||
| Notes | ADAS; 600.085; 600.082; 600.076 | Approved | no | ||
| Call Number | ADAS @ adas @ HME2016 | Serial | 2738 | ||
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| Author | German Ros; Laura Sellart; Joanna Materzynska; David Vazquez; Antonio Lopez | ||||
| Title | The SYNTHIA Dataset: A Large Collection of Synthetic Images for Semantic Segmentation of Urban Scenes | Type | Conference Article | ||
| Year | 2016 | Publication | 29th IEEE Conference on Computer Vision and Pattern Recognition | Abbreviated Journal | |
| Volume | Issue |
Pages | 3234-3243 | ||
| Keywords | Domain Adaptation; Autonomous Driving; Virtual Data; Semantic Segmentation | ||||
| Abstract | Vision-based semantic segmentation in urban scenarios is a key functionality for autonomous driving. The irruption of deep convolutional neural networks (DCNNs) allows to foresee obtaining reliable classifiers to perform such a visual task. However, DCNNs require to learn many parameters from raw images; thus, having a sufficient amount of diversified images with this class annotations is needed. These annotations are obtained by a human cumbersome labour specially challenging for semantic segmentation, since pixel-level annotations are required. In this paper, we propose to use a virtual world for automatically generating realistic synthetic images with pixel-level annotations. Then, we address the question of how useful can be such data for the task of semantic segmentation; in particular, when using a DCNN paradigm. In order to answer this question we have generated a synthetic diversified collection of urban images, named SynthCity, with automatically generated class annotations. We use SynthCity in combination with publicly available real-world urban images with manually provided annotations. Then, we conduct experiments on a DCNN setting that show how the inclusion of SynthCity in the training stage significantly improves the performance of the semantic segmentation task | ||||
| Address | Las Vegas; USA; June 2016 | ||||
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| Area | Expedition | Conference | CVPR | ||
| Notes | ADAS; 600.085; 600.082; 600.076 | Approved | no | ||
| Call Number | ADAS @ adas @ RSM2016 | Serial | 2739 | ||
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| Author | Daniel Hernandez; Alejandro Chacon; Antonio Espinosa; David Vazquez; Juan Carlos Moure; Antonio Lopez | ||||
| Title | Embedded real-time stereo estimation via Semi-Global Matching on the GPU | Type | Conference Article | ||
| Year | 2016 | Publication | 16th International Conference on Computational Science | Abbreviated Journal | |
| Volume | 80 | Issue |
Pages | 143-153 | |
| Keywords | Autonomous Driving; Stereo; CUDA; 3d reconstruction | ||||
| Abstract | Dense, robust and real-time computation of depth information from stereo-camera systems is a computationally demanding requirement for robotics, advanced driver assistance systems (ADAS) and autonomous vehicles. Semi-Global Matching (SGM) is a widely used algorithm that propagates consistency constraints along several paths across the image. This work presents a real-time system producing reliable disparity estimation results on the new embedded energy-efficient GPU devices. Our design runs on a Tegra X1 at 41 frames per second for an image size of 640x480, 128 disparity levels, and using 4 path directions for the SGM method. | ||||
| Address | San Diego; CA; USA; June 2016 | ||||
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| Area | Expedition | Conference | ICCS | ||
| Notes | ADAS; 600.085; 600.082; 600.076 | Approved | no | ||
| Call Number | ADAS @ adas @ HCE2016a | Serial | 2740 | ||
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| Author | Victor Campmany; Sergio Silva; Antonio Espinosa; Juan Carlos Moure; David Vazquez; Antonio Lopez | ||||
| Title | GPU-based pedestrian detection for autonomous driving | Type | Conference Article | ||
| Year | 2016 | Publication | 16th International Conference on Computational Science | Abbreviated Journal | |
| Volume | 80 | Issue |
Pages | 2377-2381 | |
| Keywords | Pedestrian detection; Autonomous Driving; CUDA | ||||
| Abstract | We propose a real-time pedestrian detection system for the embedded Nvidia Tegra X1 GPU-CPU hybrid platform. The pipeline is composed by the following state-of-the-art algorithms: Histogram of Local Binary Patterns (LBP) and Histograms of Oriented Gradients (HOG) features extracted from the input image; Pyramidal Sliding Window technique for foreground segmentation; and Support Vector Machine (SVM) for classification. Results show a 8x speedup in the target Tegra X1 platform and a better performance/watt ratio than desktop CUDA platforms in study. | ||||
| Address | San Diego; CA; USA; June 2016 | ||||
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| Area | Expedition | Conference | ICCS | ||
| Notes | ADAS; 600.085; 600.082; 600.076 | Approved | no | ||
| Call Number | ADAS @ adas @ CSE2016 | Serial | 2741 | ||
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| Author | Maedeh Aghaei; Mariella Dimiccoli; Petia Radeva | ||||
| Title | Multi-face tracking by extended bag-of-tracklets in egocentric photo-streams | Type | Journal Article | ||
| Year | 2016 | Publication | Computer Vision and Image Understanding | Abbreviated Journal | CVIU |
| Volume | 149 | Issue |
Pages | 146-156 | |
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| Abstract | Wearable cameras offer a hands-free way to record egocentric images of daily experiences, where social events are of special interest. The first step towards detection of social events is to track the appearance of multiple persons involved in them. In this paper, we propose a novel method to find correspondences of multiple faces in low temporal resolution egocentric videos acquired through a wearable camera. This kind of photo-stream imposes additional challenges to the multi-tracking problem with respect to conventional videos. Due to the free motion of the camera and to its low temporal resolution, abrupt changes in the field of view, in illumination condition and in the target location are highly frequent. To overcome such difficulties, we propose a multi-face tracking method that generates a set of tracklets through finding correspondences along the whole sequence for each detected face and takes advantage of the tracklets redundancy to deal with unreliable ones. Similar tracklets are grouped into the so called extended bag-of-tracklets (eBoT), which is aimed to correspond to a specific person. Finally, a prototype tracklet is extracted for each eBoT, where the occurred occlusions are estimated by relying on a new measure of confidence. We validated our approach over an extensive dataset of egocentric photo-streams and compared it to state of the art methods, demonstrating its effectiveness and robustness. | ||||
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| Notes | MILAB; | Approved | no | ||
| Call Number | Admin @ si @ ADR2016b | Serial | 2742 | ||
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| Author | Onur Ferhat; Fernando Vilariño | ||||
| Title | Low Cost Eye Tracking: The Current Panorama | Type | Journal Article | ||
| Year | 2016 | Publication | Computational Intelligence and Neuroscience | Abbreviated Journal | CIN |
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Pages | Article ID 8680541 | ||
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| Abstract | Despite the availability of accurate, commercial gaze tracker devices working with infrared (IR) technology, visible light gaze tracking constitutes an interesting alternative by allowing scalability and removing hardware requirements. Over the last years, this field has seen examples of research showing performance comparable to the IR alternatives. In this work, we survey the previous work on remote, visible light gaze trackers and analyze the explored techniques from various perspectives such as calibration strategies, head pose invariance, and gaze estimation techniques. We also provide information on related aspects of research such as public datasets to test against, open source projects to build upon, and gaze tracking services to directly use in applications. With all this information, we aim to provide the contemporary and future researchers with a map detailing previously explored ideas and the required tools. | ||||
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| Notes | MV; 605.103; 600.047; 600.097;SIAI | Approved | no | ||
| Call Number | Admin @ si @ FeV2016 | Serial | 2744 | ||
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| Author | Pedro Martins; Paulo Carvalho; Carlo Gatta | ||||
| Title | On the completeness of feature-driven maximally stable extremal regions | Type | Journal Article | ||
| Year | 2016 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
| Volume | 74 | Issue |
Pages | 9-16 | |
| Keywords | Local features; Completeness; Maximally Stable Extremal Regions | ||||
| Abstract | By definition, local image features provide a compact representation of the image in which most of the image information is preserved. This capability offered by local features has been overlooked, despite being relevant in many application scenarios. In this paper, we analyze and discuss the performance of feature-driven Maximally Stable Extremal Regions (MSER) in terms of the coverage of informative image parts (completeness). This type of features results from an MSER extraction on saliency maps in which features related to objects boundaries or even symmetry axes are highlighted. These maps are intended to be suitable domains for MSER detection, allowing this detector to provide a better coverage of informative image parts. Our experimental results, which were based on a large-scale evaluation, show that feature-driven MSER have relatively high completeness values and provide more complete sets than a traditional MSER detection even when sets of similar cardinality are considered. | ||||
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| Publisher | Elsevier B.V. | Place of Publication | Editor | ||
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| ISSN | 0167-8655 | ISBN | Medium | ||
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| Notes | LAMP;MILAB; | Approved | no | ||
| Call Number | Admin @ si @ MCG2016 | Serial | 2748 | ||
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| Author | Eugenio Alcala; Laura Sellart; Vicenc Puig; Joseba Quevedo; Jordi Saludes; David Vazquez; Antonio Lopez | ||||
| Title | Comparison of two non-linear model-based control strategies for autonomous vehicles | Type | Conference Article | ||
| Year | 2016 | Publication | 24th Mediterranean Conference on Control and Automation | Abbreviated Journal | |
| Volume | Issue |
Pages | 846-851 | ||
| Keywords | Autonomous Driving; Control | ||||
| Abstract | This paper presents the comparison of two nonlinear model-based control strategies for autonomous cars. A control oriented model of vehicle based on a bicycle model is used. The two control strategies use a model reference approach. Using this approach, the error dynamics model is developed. Both controllers receive as input the longitudinal, lateral and orientation errors generating as control outputs the steering angle and the velocity of the vehicle. The first control approach is based on a non-linear control law that is designed by means of the Lyapunov direct approach. The second approach is based on a sliding mode-control that defines a set of sliding surfaces over which the error trajectories will converge. The main advantage of the sliding-control technique is the robustness against non-linearities and parametric uncertainties in the model. However, the main drawback of first order sliding mode is the chattering, so it has been implemented a high order sliding mode control. To test and compare the proposed control strategies, different path following scenarios are used in simulation. | ||||
| Address | Athens; Greece; June 2016 | ||||
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| Area | Expedition | Conference | MED | ||
| Notes | ADAS; 600.085; 600.082; 600.076 | Approved | no | ||
| Call Number | ADAS @ adas @ ASP2016 | Serial | 2750 | ||
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| Author | Joan Mas; Alicia Fornes; Josep Llados | ||||
| Title | An Interactive Transcription System of Census Records using Word-Spotting based Information Transfer | Type | Conference Article | ||
| Year | 2016 | Publication | 12th IAPR Workshop on Document Analysis Systems | Abbreviated Journal | |
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Pages | 54-59 | ||
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| Abstract | This paper presents a system to assist in the transcription of historical handwritten census records in a crowdsourcing platform. Census records have a tabular structured layout. They consist in a sequence of rows with information of homes ordered by street address. For each household snippet in the page, the list of family members is reported. The censuses are recorded in intervals of a few years and the information of individuals in each household is quite stable from a point in time to the next one. This redundancy is used to assist the transcriber, so the redundant information is transferred from the census already transcribed to the next one. Household records are aligned from one year to the next one using the knowledge of the ordering by street address. Given an already transcribed census, a query by string word spotting is applied. Thus, names from the census in time t are used as queries in the corresponding home record in time t+1. Since the search is constrained, the obtained precision-recall values are very high, with an important reduction in the transcription time. The proposed system has been tested in a real citizen-science experience where non expert users transcribe the census data of their home town. | ||||
| Address | Santorini; Greece; April 2016 | ||||
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| Area | Expedition | Conference | DAS | ||
| Notes | DAG; 603.053; 602.006; 600.061; 600.077; 600.097 | Approved | no | ||
| Call Number | Admin @ si @ MFL2016 | Serial | 2751 | ||
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