Journal ArticleDOI
Indoor scene recognition by a mobile robot through adaptive object detection
TLDR
This paper uses concepts from information theory to propose an adaptive scheme that limits computational load by selectively guiding the search for informative objects, and results indicate that the proposed approach outperforms several state-of-the-art techniques for scene recognition.About:
This article is published in Robotics and Autonomous Systems.The article was published on 2013-09-01. It has received 69 citations till now. The article focuses on the topics: Mobile robot & Object detection.read more
Citations
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Journal ArticleDOI
Semantic mapping for mobile robotics tasks
TL;DR: An explicit analysis of the existing methods of semantic mapping is sought, and the several algorithms are categorized according to their primary characteristics, namely scalability, inference model, temporal coherence and topological map usage.
Journal ArticleDOI
Scene Recognition for Indoor Localization Using a Multi-Sensor Fusion Approach.
TL;DR: Both positioning accuracy and robustness are enhanced compared to approaches without scene constraint including commercial products such as IndoorAtlas.
Proceedings ArticleDOI
Following High-level Navigation Instructions on a Simulated Quadcopter with Imitation Learning
TL;DR: A method for following high-level navigation instructions by mapping directly from images, instructions and pose estimates to continuous low-level velocity commands for real-time control is introduced.
Journal ArticleDOI
A Taxonomy of Vision Systems for Ground Mobile Robots
Jesus Martínez-Gómez,Antonio Fernández-Caballero,Ismael García-Varea,Luis Rodríguez,Cristina Romero-González +4 more
TL;DR: A global picture of the state of the art in the area is offered and some promising research lines are discovered, namely in order to respond to the main questions posed when designing robotic vision systems.
Journal ArticleDOI
Indoor Visual Positioning Aided by CNN-Based Image Retrieval: Training-Free, 3D Modeling-Free.
TL;DR: A localization method based on image retrieval that can efficiently result in high location accuracy as well as orientation estimation and attempts to use lightweight datum to present the scene.
References
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Random Forests
TL;DR: Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the forest, and are also applicable to regression.
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Distinctive Image Features from Scale-Invariant Keypoints
TL;DR: This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene and can robustly identify objects among clutter and occlusion while achieving near real-time performance.
Proceedings ArticleDOI
Histograms of oriented gradients for human detection
Navneet Dalal,Bill Triggs +1 more
TL;DR: It is shown experimentally that grids of histograms of oriented gradient (HOG) descriptors significantly outperform existing feature sets for human detection, and the influence of each stage of the computation on performance is studied.
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Latent dirichlet allocation
TL;DR: This work proposes a generative model for text and other collections of discrete data that generalizes or improves on several previous models including naive Bayes/unigram, mixture of unigrams, and Hofmann's aspect model.
Proceedings Article
Latent Dirichlet Allocation
TL;DR: This paper proposed a generative model for text and other collections of discrete data that generalizes or improves on several previous models including naive Bayes/unigram, mixture of unigrams, and Hof-mann's aspect model, also known as probabilistic latent semantic indexing (pLSI).