Vision-based navigation and environmental representations with an omnidirectional camera

Gaspar, José António; Winters, Niall; Santos-Victor, José

doi:10.1109/70.897802

Cited by 248 publications

(136 citation statements)

References 28 publications

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“…Let us consider, for example, a case of a view-based localization of a mobile platform using a set of panoramic images to represent the environment [8,9,1,11]. Due to the wide field-of-view, it is almost impossible to obtain training images without outliers (e.g., people moving around).…”

Section: Introductionmentioning

confidence: 99%

A Robust PCA Algorithm for Building Representations from Panoramic Images

Skočaj

Bischof

Leonardis

2002

Computer Vision — ECCV 2002

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Abstract. Appearance-based modeling of objects and scenes using PCA has been successfully applied in many recognition tasks. Robust methods which have made the recognition stage less susceptible to outliers, occlusions, and varying illumination have further enlarged the domain of applicability. However, much less research has been done in achieving robustness in the learning stage. In this paper, we propose a novel robust PCA method for obtaining a consistent subspace representation in the presence of outlying pixels in the training images. The method is based on the EM algorithm for estimation of principal subspaces in the presence of missing data. By treating the outlying points as missing pixels, we arrive at a robust PCA representation. We demonstrate experimentally that the proposed method is efficient. In addition, we apply the method to a set of panoramic images to build a representation that enables surveillance and view-based mobile robot localization.

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Section: Introductionmentioning

confidence: 99%

A Robust PCA Algorithm for Building Representations from Panoramic Images

Skočaj

Bischof

Leonardis

2002

Computer Vision — ECCV 2002

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“…Work on place recognition in robotics has ranged over matching SIFT features across images [37] or other derived measures of distinctiveness for places such as Fourier signatures [18], subspace representations [11], and color histograms [31]. These methods have the disadvantage of not being able to generalize and also are invariant to perspective mainly through the use of omnidirectional images.…”

Section: Related Workmentioning

confidence: 99%

PLISS: Detecting and Labeling Places Using Online Change-Point Detection

Ranganathan¹

2010

Robotics: Science and Systems VI

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Abstract-We present PLISS (Place Labeling through Image Sequence Segmentation), a novel technique for place recognition and categorization from visual cues. PLISS operates on video or image streams and works by segmenting it into pieces corresponding to distinct places in the environment. An online Bayesian change-point detection framework that detects changes to model parameters is used to segment the image stream. Unlike current place recognition methods, in addition to using previously learned place models for labeling, PLISS can also detect and learn a previously unknown place or place category in an online manner. Moreover, since both the inferred boundaries of places (change-points) and the place labels are fully probabilistic, they can indicate when the inference is uncertain. New places and categories are detected using a systematic statistical hypothesis testing framework. We present extensive experiments on a large and difficult image dataset. We validate our claims by comparing results obtained using different types of features and by comparing results from PLISS against the state of the art.

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“…The sensor is located in front (i.e., the moving direction). Vision is used in many applications such as optical motion planning mapping [6], [8], or the motion sensors themselves [4], [3], [11].…”

Section: Concepts and Premisesmentioning

confidence: 99%

A Collision Control Strategy for Multiple Moving Robots

Kamkarian

Hexmoor

2013

Advances in Intelligent Systems and Computing

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Abstract. We present a solution to prevent collisions among robots that are moving toward their respective goals. A robot may start moving at any time from its station to its goal. For a moving robot, the probability of conflict increases proportionately to the complexity of other robots' respective routes. In terms of lowering possibilities of collision, a proper strategy for controlling robot behaviors before encounters is essential. Prior research presented a negotiation-based solution through a broadcasting method. In our solution, we assume robots are unable or unwilling to negotiate or broadcast data among one another. They should possess a strategy to detect and predict conflict zones, and hence determine strategies to avoid collisions independently.

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Vision-based navigation and environmental representations with an omnidirectional camera

Cited by 248 publications

References 28 publications

A Robust PCA Algorithm for Building Representations from Panoramic Images

A Robust PCA Algorithm for Building Representations from Panoramic Images

PLISS: Detecting and Labeling Places Using Online Change-Point Detection

A Collision Control Strategy for Multiple Moving Robots

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