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Author |
Arnau Ramisa; David Aldavert; Shrihari Vasudevan; Ricardo Toledo; Ramon Lopez de Mantaras |
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Title |
The IIIA30 MObile Robot Object Recognition Datset |
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Conference Article |
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Year |
2011 |
Publication |
11th Portuguese Robotics Open |
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Object perception is a key feature in order to make mobile robots able to perform high-level tasks. However, research aimed at addressing the constraints and limitations encountered in a mobile robotics scenario, like low image resolution, motion blur or tight computational constraints, is still very scarce. In order to facilitate future research in this direction, in this work we present an object detection and recognition dataset acquired using a mobile robotic platform. As a baseline for the dataset, we evaluated the cascade of weak classifiers object detection method from Viola and Jones. |
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Lisboa |
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Robotica |
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RV;ADAS |
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no |
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Admin @ si @ RAV2011 |
Serial |
1777 |
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Author |
Mohammad Rouhani; Angel Sappa |
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Title |
Implicit B-Spline Fitting Using the 3L Algorithm |
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Conference Article |
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Year |
2011 |
Publication |
18th IEEE International Conference on Image Processing |
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893-896 |
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Brussels, Belgium |
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ICIP |
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ADAS |
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no |
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Admin @ si @ RoS2011a; ADAS @ adas @ |
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1782 |
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Author |
Marçal Rusiñol; David Aldavert; Ricardo Toledo; Josep Llados |
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Title |
Browsing Heterogeneous Document Collections by a Segmentation-Free Word Spotting Method |
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Conference Article |
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Year |
2011 |
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11th International Conference on Document Analysis and Recognition |
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63-67 |
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In this paper, we present a segmentation-free word spotting method that is able to deal with heterogeneous document image collections. We propose a patch-based framework where patches are represented by a bag-of-visual-words model powered by SIFT descriptors. A later refinement of the feature vectors is performed by applying the latent semantic indexing technique. The proposed method performs well on both handwritten and typewritten historical document images. We have also tested our method on documents written in non-Latin scripts. |
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Beijing, China |
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ICDAR |
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DAG;ADAS |
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no |
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Admin @ si @ RAT2011 |
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1788 |
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Author |
Mohammad Rouhani; Angel Sappa |
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Title |
Correspondence Free Registration through a Point-to-Model Distance Minimization |
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Conference Article |
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2011 |
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13th IEEE International Conference on Computer Vision |
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2150-2157 |
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This paper presents a novel formulation, which derives in a smooth minimization problem, to tackle the rigid registration between a given point set and a model set. Unlike most of the existing works, which are based on minimizing a point-wise correspondence term, we propose to describe the model set by means of an implicit representation. It allows a new definition of the registration error, which works beyond the point level representation. Moreover, it could be used in a gradient-based optimization framework. The proposed approach consists of two stages. Firstly, a novel formulation is proposed that relates the registration parameters with the distance between the model and data set. Secondly, the registration parameters are obtained by means of the Levengberg-Marquardt algorithm. Experimental results and comparisons with state of the art show the validity of the proposed framework. |
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Barcelona |
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1550-5499 |
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978-1-4577-1101-5 |
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ICCV |
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ADAS |
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no |
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Admin @ si @ RoS2011b; ADAS @ adas @ |
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1832 |
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Author |
Naveen Onkarappa; Sujay M. Veerabhadrappa; Angel Sappa |
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Title |
Optical Flow in Onboard Applications: A Study on the Relationship Between Accuracy and Scene Texture |
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Conference Article |
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Year |
2012 |
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4th International Conference on Signal and Image Processing |
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221 |
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257-267 |
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Optical flow has got a major role in making advanced driver assistance systems (ADAS) a reality. ADAS applications are expected to perform efficiently in all kinds of environments, those are highly probable, that one can drive the vehicle in different kinds of roads, times and seasons. In this work, we study the relationship of optical flow with different roads, that is by analyzing optical flow accuracy on different road textures. Texture measures such as TeX , TeX and TeX are evaluated for this purpose. Further, the relation of regularization weight to the flow accuracy in the presence of different textures is also analyzed. Additionally, we present a framework to generate synthetic sequences of different textures in ADAS scenarios with ground-truth optical flow. |
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Coimbatore, India |
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1876-1100 |
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978-81-322-0996-6 |
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ICSIP |
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ADAS |
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no |
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Call Number |
Admin @ si @ OVS2012 |
Serial |
2356 |
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Author |
Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Maria Vanrell; Antonio Lopez |
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Title |
Color Attributes for Object Detection |
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Conference Article |
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Year |
2012 |
Publication |
25th IEEE Conference on Computer Vision and Pattern Recognition |
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Pages |
3306-3313 |
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Keywords |
pedestrian detection |
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Abstract |
State-of-the-art object detectors typically use shape information as a low level feature representation to capture the local structure of an object. This paper shows that early fusion of shape and color, as is popular in image classification,
leads to a significant drop in performance for object detection. Moreover, such approaches also yields suboptimal results for object categories with varying importance of color and shape.
In this paper we propose the use of color attributes as an explicit color representation for object detection. Color attributes are compact, computationally efficient, and when combined with traditional shape features provide state-ofthe-
art results for object detection. Our method is tested on the PASCAL VOC 2007 and 2009 datasets and results clearly show that our method improves over state-of-the-art techniques despite its simplicity. We also introduce a new dataset consisting of cartoon character images in which color plays a pivotal role. On this dataset, our approach yields a significant gain of 14% in mean AP over conventional state-of-the-art methods. |
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Providence; Rhode Island; USA; |
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IEEE Xplore |
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1063-6919 |
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978-1-4673-1226-4 |
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CVPR |
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Notes |
ADAS; CIC; |
Approved |
no |
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Call Number |
Admin @ si @ KRW2012 |
Serial |
1935 |
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Author |
G.D. Evangelidis; Ferran Diego; Joan Serrat; Antonio Lopez |
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Title |
Slice Matching for Accurate Spatio-Temporal Alignment |
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Conference Article |
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Year |
2011 |
Publication |
In ICCV Workshop on Visual Surveillance |
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Keywords |
video alignment |
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Video synchronization and alignment is a rather recent topic in computer vision. It usually deals with the problem of aligning sequences recorded simultaneously by static, jointly- or independently-moving cameras. In this paper, we investigate the more difficult problem of matching videos captured at different times from independently-moving cameras, whose trajectories are approximately coincident or parallel. To this end, we propose a novel method that pixel-wise aligns videos and allows thus to automatically highlight their differences. This primarily aims at visual surveillance but the method can be adopted as is by other related video applications, like object transfer (augmented reality) or high dynamic range video. We build upon a slice matching scheme to first synchronize the sequences, while we develop a spatio-temporal alignment scheme to spatially register corresponding frames and refine the temporal mapping. We investigate the performance of the proposed method on videos recorded from vehicles driven along different types of roads and compare with related previous works. |
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VS |
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ADAS |
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no |
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Admin @ si @ EDS2011; ADAS @ adas @ eds2011a |
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1861 |
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Permanent link to this record |
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Author |
Gemma Roig; Xavier Boix; F. de la Torre; Joan Serrat; C. Vilella |
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Title |
Hierarchical CRF with product label spaces for parts-based Models |
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Conference Article |
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Year |
2011 |
Publication |
IEEE Conference on Automatic Face and Gesture Recognition |
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Pages |
657-664 |
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Keywords |
Shape; Computational modeling; Principal component analysis; Random variables; Color; Upper bound; Facial features |
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Abstract |
Non-rigid object detection is a challenging an open research problem in computer vision. It is a critical part in many applications such as image search, surveillance, human-computer interaction or image auto-annotation. Most successful approaches to non-rigid object detection make use of part-based models. In particular, Conditional Random Fields (CRF) have been successfully embedded into a discriminative parts-based model framework due to its effectiveness for learning and inference (usually based on a tree structure). However, CRF-based approaches do not incorporate global constraints and only model pairwise interactions. This is especially important when modeling object classes that may have complex parts interactions (e.g. facial features or body articulations), because neglecting them yields an oversimplified model with suboptimal performance. To overcome this limitation, this paper proposes a novel hierarchical CRF (HCRF). The main contribution is to build a hierarchy of part combinations by extending the label set to a hierarchy of product label spaces. In order to keep the inference computation tractable, we propose an effective method to reduce the new label set. We test our method on two applications: facial feature detection on the Multi-PIE database and human pose estimation on the Buffy dataset. |
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Santa Barbara, CA, USA, 2011 |
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ADAS |
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no |
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Call Number |
Admin @ si @ RBT2011 |
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1862 |
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Author |
Yainuvis Socarras; Sebastian Ramos; David Vazquez; Antonio Lopez; Theo Gevers |
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Title |
Adapting Pedestrian Detection from Synthetic to Far Infrared Images |
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Conference Article |
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2013 |
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ICCV Workshop on Visual Domain Adaptation and Dataset Bias |
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Domain Adaptation; Far Infrared; Pedestrian Detection |
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We present different techniques to adapt a pedestrian classifier trained with synthetic images and the corresponding automatically generated annotations to operate with far infrared (FIR) images. The information contained in this kind of images allow us to develop a robust pedestrian detector invariant to extreme illumination changes. |
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Sydney; Australia; December 2013 |
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Sydney, Australy |
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English |
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ICCVW-VisDA |
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ADAS; 600.054; 600.055; 600.057; 601.217;ISE |
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no |
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ADAS @ adas @ SRV2013 |
Serial |
2334 |
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Author |
Patricia Marquez; Debora Gil; Aura Hernandez-Sabate |
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Title |
Evaluation of the Capabilities of Confidence Measures for Assessing Optical Flow Quality |
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Conference Article |
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Year |
2013 |
Publication |
ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars |
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624-631 |
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Assessing Optical Flow (OF) quality is essential for its further use in reliable decision support systems. The absence of ground truth in such situations leads to the computation of OF Confidence Measures (CM) obtained from either input or output data. A fair comparison across the capabilities of the different CM for bounding OF error is required in order to choose the best OF-CM pair for discarding points where OF computation is not reliable. This paper presents a statistical probabilistic framework for assessing the quality of a given CM. Our quality measure is given in terms of the percentage of pixels whose OF error bound can not be determined by CM values. We also provide statistical tools for the computation of CM values that ensures a given accuracy of the flow field. |
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Sydney; Australia; December 2013 |
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CVTT:E2M |
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IAM; ADAS; 600.044; 600.057; 601.145 |
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no |
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Call Number |
Admin @ si @ MGH2013b |
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2351 |
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