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Hough Regions for Joining Instance Localization and Segmentation [chapter]

Hayko Riemenschneider, Sabine Sternig, Michael Donoser, Peter M. Roth, Horst Bischof
2012 Lecture Notes in Computer Science  
We introduce Hough Regions by formulating the problem of Hough space analysis as Bayesian labeling of a random field.  ...  Our novel approach is attachable to any of the available generalized Hough voting methods.  ...  Our starting point is any generalized Hough voting method like the Implicit Shape Model (ISM) [5] , Hough Forests [17] or the max-margin Hough transform [18] .  ... 
doi:10.1007/978-3-642-33712-3_19 fatcat:4uaeqeyoxfhblffzkupe5swhwi

Overview of Environment Perception for Intelligent Vehicles

Hao Zhu, Ka-Veng Yuen, Lyudmila Mihaylova, Henry Leung
2017 IEEE transactions on intelligent transportation systems (Print)  
The state-of-the-art algorithms and modeling methods for intelligent vehicles are given, with a summary of their pros and cons.  ...  A special attention is paid to methods for lane and road detection, traffic sign recognition, vehicle tracking, behavior analysis, and scene understanding.  ...  scenes and 315 pictures of office scenes • Performance evaluate: segmentation results, ROC curves N/A Couples topic models originally developed for text analysis with spatial transformations; consistently  ... 
doi:10.1109/tits.2017.2658662 fatcat:mvfmou6ydjafnjq3ddk5rqi5ia

Synthetic Data for Text Localisation in Natural Images

Ankush Gupta, Andrea Vedaldi, Andrew Zisserman
2016 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
This engine overlays synthetic text to existing background images in a natural way, accounting for the local 3D scene geometry.  ...  In this paper we introduce a new method for text detection in natural images.  ...  While this construction may sound abstract, it is actually a common one, implemented for example by Implicit Shape Models (ISM) [28] and Hough voting [16] .  ... 
doi:10.1109/cvpr.2016.254 dblp:conf/cvpr/GuptaVZ16 fatcat:s23mmcbbjfdsznsnlpr4f4rlsi

On detection of multiple object instances using hough transforms

Olga Barinova, Victor Lempitsky, Pushmeet Kohli
2010 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition  
In the paper, we develop a new probabilistic framework that is in many ways related to Hough transform, sharing its simplicity and wide applicability.  ...  As a result, the experiments demonstrate a significant improvement in detection accuracy both for the classical task of straight line detection and for a more modern category-level (pedestrian) detection  ...  Notably, the new model can reuse the training procedures and the vote representations developed in previous works on Hough-based detection, such as Implicit Shape models [12] or Hough forests [7] .  ... 
doi:10.1109/cvpr.2010.5539905 dblp:conf/cvpr/BarinovaLK10 fatcat:krsqmeuaanfpzmlp7unmptqm34

Synthetic Data for Text Localisation in Natural Images [article]

Ankush Gupta and Andrea Vedaldi and Andrew Zisserman
2016 arXiv   pre-print
This engine overlays synthetic text to existing background images in a natural way, accounting for the local 3D scene geometry.  ...  In this paper we introduce a new method for text detection in natural images.  ...  While this construction may sound abstract, it is actually a common one, implemented for example by Implicit Shape Models (ISM) [28] and Hough voting [16] .  ... 
arXiv:1604.06646v1 fatcat:jioihqy3dbc5vj34xvinivpyue

Text Detection and Recognition in Imagery: A Survey

Qixiang Ye, David Doermann
2015 IEEE Transactions on Pattern Analysis and Machine Intelligence  
Special issues associated with the enhancement of degraded text and the processing of video text, multi-oriented, perspectively distorted and multilingual text are also addressed.  ...  This paper analyzes, compares, and contrasts technical challenges, methods, and the performance of text detection and recognition research in color imagery.  ...  Part based implicit models have explored for distorted character recognition [192] , [195] . Shi et al.  ... 
doi:10.1109/tpami.2014.2366765 pmid:26352454 fatcat:cuz3qhkglnahdebxqptbsgpjmm

Efficient regression of general-activity human poses from depth images

Ross Girshick, Jamie Shotton, Pushmeet Kohli, Antonio Criminisi, Andrew Fitzgibbon
2011 2011 International Conference on Computer Vision  
We present a new approach to general-activity human pose estimation from depth images, building on Hough forests.  ...  We extend existing techniques in several ways: real time prediction of multiple 3D joints, explicit learning of voting weights, vote compression to allow larger training sets, and a comparison of several  ...  A related problem is solved in object localization. For example, in the implicit shape model (ISM) [11] , visual words are used to learn voting offsets to predict 2D object centers.  ... 
doi:10.1109/iccv.2011.6126270 dblp:conf/iccv/GirshickSKCF11 fatcat:yuh7acrkfvh5loltw5tnxt7fqu

SEED: Semantics Enhanced Encoder-Decoder Framework for Scene Text Recognition

Zhi Qiao, Yu Zhou, Dongbao Yang, Yucan Zhou, Weiping Wang
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
Scene text recognition is a hot research topic in computer vision.  ...  Recently, many recognition methods based on the encoder-decoder framework have been proposed, and they can handle scene texts of perspective distortion and curve shape.  ...  [50, 49] use sliding windows with HOG descriptors, and [55, 3] use Hough voting with random forest classifier.  ... 
doi:10.1109/cvpr42600.2020.01354 dblp:conf/cvpr/QiaoZYZ020 fatcat:4xpql4riqvbqbifthdhw7n3nlm

SEED: Semantics Enhanced Encoder-Decoder Framework for Scene Text Recognition [article]

Zhi Qiao, Yu Zhou, Dongbao Yang, Yucan Zhou, Weiping Wang
2020 arXiv   pre-print
Scene text recognition is a hot research topic in computer vision.  ...  Recently, many recognition methods based on the encoder-decoder framework have been proposed, and they can handle scene texts of perspective distortion and curve shape.  ...  [50, 49] use sliding windows with HOG descriptors, and [55, 3] use Hough voting with random forest classifier.  ... 
arXiv:2005.10977v1 fatcat:7ik6bxivyrfuzeiwnvcoqk5azq

Arabic Cursive Text Recognition from Natural Scene Images

Saad Ahmed, Saeeda Naz, Muhammad Razzak, Rubiyah Yusof
2019 Applied Sciences  
This paper presents a comprehensive survey on Arabic cursive scene text recognition.  ...  Among cursive scripts, Arabic scene text recognition is contemplated as a more challenging problem due to joined writing, same character variations, a large number of ligatures, the number of baselines  ...  More than one shape of a character increases the complexity in character recognition. 2.  ... 
doi:10.3390/app9020236 fatcat:jowekkffqrelvj3mk4324uj2v4

A survey of Hough Transform

Priyanka Mukhopadhyay, Bidyut B. Chaudhuri
2015 Pattern Recognition  
In 1962 Hough earned the patent for a method [1], popularly called Hough Transform (HT) that efficiently identifies lines in images.  ...  Our survey, along with more than 200 references, will help the researchers and students to get a comprehensive view on HT and guide them in applying it properly to their problems of interest.  ...  Bhandarkar [79] presented a fuzzy-probabilistic model of the GHT called Weighted GHT (WGHT) where each match of a scene feature with a model feature is assigned a weight based on the Table 1 Comparison  ... 
doi:10.1016/j.patcog.2014.08.027 fatcat:oye56pu2mrastlppxds6cggvue

Fast PRISM: Branch and Bound Hough Transform for Object Class Detection

Alain Lehmann, Bastian Leibe, Luc Van Gool
2010 International Journal of Computer Vision  
The PRincipled Implicit Shape Model (PRISM) overcomes these problems by interpreting Hough voting as a dual implementation of linear slidingwindow detection.  ...  This approach has been made popular by the Implicit Shape Model (ISM) and has been adopted many times.  ...  This contribution plays out on the level of object modelling and motivates the name PRISM: PRincipled Implicit Shape Model.  ... 
doi:10.1007/s11263-010-0342-x fatcat:fenhe3yqyzb3hn2ncblydaxacy

Visual Object Recognition

Kristen Grauman, Bastian Leibe
2011 Synthesis Lectures on Artificial Intelligence and Machine Learning  
connected constellations; pyramid match kernels; detection via sliding windows; Hough voting; Generalized distance transform; the Implicit Shape Model; the Deformable Part-based Model vii Contents  ...  outliers in correspondences, RANSAC and the Generalized Hough transform; window-based descriptors, histograms of oriented gradients and rectangular features; part-based models, star graph models and fully  ...  Kristen Grauman's work on this project was supported in part by NSF CAREER IIS-#0747356, a Microsoft Research New Faculty Fellowship, and the Henry Luce Foundation.  ... 
doi:10.2200/s00332ed1v01y201103aim011 fatcat:fhz7aokkfjav7fuauuorfstq4y

Fast Pedestrian Detection by Cascaded Random Forest with Dominant Orientation Templates

Danhang Tang, Yang Liu, Tae-kyun Kim
2012 Procedings of the British Machine Vision Conference 2012  
By combining a holistic and a patch-based detectors in a cascade manner, we accelerate the detection speed of Hough Forest, a prior-art using Random Forest and HOG, by about 20 times.  ...  We propose a novel template-matching split function using DOT for Random Forest. It divides a feature space in a non-linear manner, but has a very low complexity up to binary bit-wise operations.  ...  Inspired by the Implicit Shape Model [19] , Gall [12] , which is a cascade of holistic and part-based detectors, has been widely considered as a state-of-the-art baseline. Feature.  ... 
doi:10.5244/c.26.58 dblp:conf/bmvc/TangLK12 fatcat:o757ztzkefeyhj5kep73dy3mey

Social interaction discovery by statistical analysis of F-formations

Marco Cristani, Loris Bazzani, Giulia Paggetti, Andrea Fossati, Diego Tosato, Alessio Del Bue, Gloria Menegaz, Vittorio Murino
2011 Procedings of the British Machine Vision Conference 2011  
Our system takes as input the positions of the people in a scene and their (head) orientations; then, employing a voting strategy based on the Hough transform, it recognizes F-formations and the individuals  ...  associated with them.  ...  This algorithm is based on a Hough-voting strategy, which lies between an implicit shape model [21] , where weighted local features vote for a location in the image plane, and a mere generalized Hough  ... 
doi:10.5244/c.25.23 dblp:conf/bmvc/CristaniBPFTBMM11 fatcat:f2kvc42ubbeydlelvynpwhvjyu
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