Records |
Author |
Jiaolong Xu; David Vazquez; Krystian Mikolajczyk; Antonio Lopez |
Title |
Hierarchical online domain adaptation of deformable part-based models |
Type ![sorted by Type field, descending order (down)](img/sort_desc.gif) |
Conference Article |
Year |
2016 |
Publication |
IEEE International Conference on Robotics and Automation |
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Issue |
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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. |
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Stockholm; Sweden; May 2016 |
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ICRA |
Notes |
ADAS; 600.085; 600.082; 600.076 |
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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 ![sorted by Type field, descending order (down)](img/sort_desc.gif) |
Conference Article |
Year |
2016 |
Publication |
3rd IberSPEECH |
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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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Lisboa; Portugal; November 2016 |
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IberSPEECH |
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DAG; MV; 600.097;SIAI |
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no |
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Admin @ si @MLF2016 |
Serial |
2813 |
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Author |
Gloria Fernandez Esparrach; Jorge Bernal; Cristina Rodriguez de Miguel; Debora Gil; Fernando Vilariño; Henry Cordova; Cristina Sanchez Montes; I.Araujo ; Maria Lopez Ceron; J.Llach; F. Javier Sanchez |
Title |
Colonic polyps are correctly identified by a computer vision method using wm-dova energy maps |
Type ![sorted by Type field, descending order (down)](img/sort_desc.gif) |
Conference Article |
Year |
2015 |
Publication |
Proceedings of 23 United European- UEG Week 2015 |
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UEG |
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MV; IAM; 600.075;SIAI |
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no |
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Admin @ si @ FBR2015 |
Serial |
2732 |
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Author |
Aleksandr Setkov; Fabio Martinez Carillo; Michele Gouiffes; Christian Jacquemin; Maria Vanrell; Ramon Baldrich |
Title |
DAcImPro: A Novel Database of Acquired Image Projections and Its Application to Object Recognition |
Type ![sorted by Type field, descending order (down)](img/sort_desc.gif) |
Conference Article |
Year |
2015 |
Publication |
Advances in Visual Computing. Proceedings of 11th International Symposium, ISVC 2015 Part II |
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Volume |
9475 |
Issue |
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Pages |
463-473 |
Keywords |
Projector-camera systems; Feature descriptors; Object recognition |
Abstract |
Projector-camera systems are designed to improve the projection quality by comparing original images with their captured projections, which is usually complicated due to high photometric and geometric variations. Many research works address this problem using their own test data which makes it extremely difficult to compare different proposals. This paper has two main contributions. Firstly, we introduce a new database of acquired image projections (DAcImPro) that, covering photometric and geometric conditions and providing data for ground-truth computation, can serve to evaluate different algorithms in projector-camera systems. Secondly, a new object recognition scenario from acquired projections is presented, which could be of a great interest in such domains, as home video projections and public presentations. We show that the task is more challenging than the classical recognition problem and thus requires additional pre-processing, such as color compensation or projection area selection. |
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Springer International Publishing |
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LNCS |
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0302-9743 |
ISBN |
978-3-319-27862-9 |
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ISVC |
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CIC |
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no |
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Admin @ si @ SMG2015 |
Serial |
2736 |
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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 ![sorted by Type field, descending order (down)](img/sort_desc.gif) |
Conference Article |
Year |
2016 |
Publication |
GPU Technology Conference |
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Pages |
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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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GTC |
Notes |
ADAS; 600.085; 600.082; 600.076 |
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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 ![sorted by Type field, descending order (down)](img/sort_desc.gif) |
Conference Article |
Year |
2016 |
Publication |
GPU Technology Conference |
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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 |
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Silicon Valley; San Francisco; USA; April 2016 |
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GTC |
Notes |
ADAS; 600.085; 600.082; 600.076 |
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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 ![sorted by Type field, descending order (down)](img/sort_desc.gif) |
Conference Article |
Year |
2016 |
Publication |
29th IEEE Conference on Computer Vision and Pattern Recognition |
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Issue |
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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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CVPR |
Notes |
ADAS; 600.085; 600.082; 600.076 |
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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 ![sorted by Type field, descending order (down)](img/sort_desc.gif) |
Conference Article |
Year |
2016 |
Publication |
16th International Conference on Computational Science |
Abbreviated Journal |
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Volume |
80 |
Issue |
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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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ICCS |
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ADAS; 600.085; 600.082; 600.076 |
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no |
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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 ![sorted by Type field, descending order (down)](img/sort_desc.gif) |
Conference Article |
Year |
2016 |
Publication |
16th International Conference on Computational Science |
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80 |
Issue |
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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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ADAS; 600.085; 600.082; 600.076 |
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no |
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ADAS @ adas @ CSE2016 |
Serial |
2741 |
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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 ![sorted by Type field, descending order (down)](img/sort_desc.gif) |
Conference Article |
Year |
2016 |
Publication |
24th Mediterranean Conference on Control and Automation |
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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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MED |
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ADAS; 600.085; 600.082; 600.076 |
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no |
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ADAS @ adas @ ASP2016 |
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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 ![sorted by Type field, descending order (down)](img/sort_desc.gif) |
Conference Article |
Year |
2016 |
Publication |
12th IAPR Workshop on Document Analysis Systems |
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54-59 |
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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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DAS |
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DAG; 603.053; 602.006; 600.061; 600.077; 600.097 |
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no |
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Admin @ si @ MFL2016 |
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2751 |
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Author |
Juan Ignacio Toledo; Alicia Fornes; Jordi Cucurull; Josep Llados |
Title |
Election Tally Sheets Processing System |
Type ![sorted by Type field, descending order (down)](img/sort_desc.gif) |
Conference Article |
Year |
2016 |
Publication |
12th IAPR Workshop on Document Analysis Systems |
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364-368 |
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In paper based elections, manual tallies at polling station level produce myriads of documents. These documents share a common form-like structure and a reduced vocabulary worldwide. On the other hand, each tally sheet is filled by a different writer and on different countries, different scripts are used. We present a complete document analysis system for electoral tally sheet processing combining state of the art techniques with a new handwriting recognition subprocess based on unsupervised feature discovery with Variational Autoencoders and sequence classification with BLSTM neural networks. The whole system is designed to be script independent and allows a fast and reliable results consolidation process with reduced operational cost. |
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Santorini; Greece; April 2016 |
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DAG; 602.006; 600.061; 601.225; 600.077; 600.097 |
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TFC2016 |
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2752 |
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Author |
Anders Hast; Alicia Fornes |
Title |
A Segmentation-free Handwritten Word Spotting Approach by Relaxed Feature Matching |
Type ![sorted by Type field, descending order (down)](img/sort_desc.gif) |
Conference Article |
Year |
2016 |
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12th IAPR Workshop on Document Analysis Systems |
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150-155 |
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The automatic recognition of historical handwritten documents is still considered challenging task. For this reason, word spotting emerges as a good alternative for making the information contained in these documents available to the user. Word spotting is defined as the task of retrieving all instances of the query word in a document collection, becoming a useful tool for information retrieval. In this paper we propose a segmentation-free word spotting approach able to deal with large document collections. Our method is inspired on feature matching algorithms that have been applied to image matching and retrieval. Since handwritten words have different shape, there is no exact transformation to be obtained. However, the sufficient degree of relaxation is achieved by using a Fourier based descriptor and an alternative approach to RANSAC called PUMA. The proposed approach is evaluated on historical marriage records, achieving promising results. |
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Santorini; Greece; April 2016 |
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DAG; 602.006; 600.061; 600.077; 600.097 |
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HaF2016 |
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2753 |
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Author |
Daniel Hernandez; Antonio Espinosa; David Vazquez; Antonio Lopez; Juan Carlos Moure |
Title |
GPU-accelerated real-time stixel computation |
Type ![sorted by Type field, descending order (down)](img/sort_desc.gif) |
Conference Article |
Year |
2017 |
Publication |
IEEE Winter Conference on Applications of Computer Vision |
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1054-1062 |
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Autonomous Driving; GPU; Stixel |
Abstract |
The Stixel World is a medium-level, compact representation of road scenes that abstracts millions of disparity pixels into hundreds or thousands of stixels. The goal of this work is to implement and evaluate a complete multi-stixel estimation pipeline on an embedded, energyefficient, GPU-accelerated device. This work presents a full GPU-accelerated implementation of stixel estimation that produces reliable results at 26 frames per second (real-time) on the Tegra X1 for disparity images of 1024×440 pixels and stixel widths of 5 pixels, and achieves more than 400 frames per second on a high-end Titan X GPU card. |
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Santa Rosa; CA; USA; March 2017 |
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WACV |
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ADAS; 600.118 |
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ADAS @ adas @ HEV2017b |
Serial |
2812 |
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Author |
Marçal Rusiñol; J. Chazalon; Jean-Marc Ogier |
Title |
Filtrage de descripteurs locaux pour l'amélioration de la détection de documents |
Type ![sorted by Type field, descending order (down)](img/sort_desc.gif) |
Conference Article |
Year |
2016 |
Publication |
Colloque International Francophone sur l'Écrit et le Document |
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Keywords |
Local descriptors; mobile capture; document matching; keypoint selection |
Abstract |
In this paper we propose an effective method aimed at reducing the amount of local descriptors to be indexed in a document matching framework.In an off-line training stage, the matching between the model document and incoming images is computed retaining the local descriptors from the model that steadily produce good matches. We have evaluated this approach by using the ICDAR2015 SmartDOC dataset containing near 25000 images from documents to be captured by a mobile device. We have tested the performance of this filtering step by using ORB and SIFT local detectors and descriptors. The results show an important gain both in quality of the final matching as well as in time and space requirements. |
Address |
Toulouse; France; March 2016 |
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CIFED |
Notes |
DAG; 600.084; 600.077 |
Approved |
no |
Call Number |
Admin @ si @ RCO2016 |
Serial |
2755 |
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