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We develop and analyze an unsupervised and domain-independent method for extracting keywords from single documents. Our approach differs from the previous ones in the way of identifying candidate keywords, pruning the list of candidate keywords with several filtering heuristics and selecting keywords from the list of candidate keywords according to dynamic threshold functions. We were able to obtain...
Autonomous service mobile robots need to consistently, accurately, and robustly localize in human environments despite changes to such environments over time. Episodic non-Markov Localization addresses the challenge of localization in such changing environments by classifying observations as arising from Long-Term, Short-Term, or Dynamic Features. However, in order to do so, EnML relies on an estimate...
An algorithm for the robust detection and recognition of gestures for the interaction between human and a domestic floor cleaner robot is presented. The gestures are selected through a user study, in which the participants are asked to show natural gestures to the robot in given specific interaction scenarios. The gestures selected are those repeated by majority of participants and consist both commanding...
As long as visual features for recognition are known in advance and remain static due to a controlled environment, object tracking is state-of-the-art. Tracking objects in dynamically changing environments is still a challenge. Even harder is the tracking of moving objects with a moving camera. Our algorithm realizes a deterministic approach to track any 2D-features representable in a general way...
In this paper we present a topological map building algorithm based on a Vocabulary Tree that is robust to features present in dynamic or similar environments. The algorithm recognises incorrect loop closures, not supported by the odometry, and uses this information to update the feature weights in the tree to suppress further associations from these features. Two methods of adjusting these feature...
This paper presents a method for detecting people from images taken with a camera mounted on a robot. The purpose of the detection is avoiding people collision while robot is moving within an unknown environment. It combines two algorithms for this purpose. First, the appearance of people is learned using a set of Haar-like features and the Adaboost algorithm. This information is embedded by building...
This paper describes a visual odometry algorithm for estimating frame-to-frame camera motion from successive stereo image pairs. The algorithm differs from most visual odometry algorithms in two key respects: (1) it makes no prior assumptions about camera motion, and (2) it operates on dense disparity images computed by a separate stereo algorithm. This algorithm has been tested on many platforms,...
A major issue in the field of mobile robotics today is the detection and tracking of moving objects (DATMO) from a moving observer. In dynamic and highly populated environments, this problem presents a complex and computationally demanding task. It can be divided in sub-problems such as robotpsilas relative motion compensation, feature extraction, measurement clustering, data association and targetspsila...
Performance of face recognition system has not been satisfied due to the change of illumination on facial image. Thus, there were many proposals that dealing with illumination compensation in face recognition in the past decades. In this paper, we propose a wavelet based illumination invariant algorithm based on the illumination-reflectance model. The proposed method aims to remove illumination component...
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