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Real-time detection of a speaker and speaker's location is a challenging task, which is usually addressed by processing acoustic/visual information. However, it is a well-known fact that when a person speaks, the lip and head movements can also be used to detect the speaker and location. This paper proposes a speaker detection system using visual prosody information (e.g. head and lip movements) in...
Map retrieval, the problem of similarity search over a large collection of 3D pointset maps previously built by mobile robots, is crucial for autonomous navigation in indoor and outdoor environments. Bag-of-words (BoW) methods constitute a popular approach to map retrieval; however, these methods have extremely limited descriptive ability because they ignore the spatial layout information of the local...
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...
This paper presents preliminary investigations on the evolution of indirect communication between two agents. In the future, behaviours of robots in the RoboCup1 competition should resemble the behaviours of the human players. One common trait of this behaviour is the indirect communication. Within the human-robot-interaction, indirect communication can either be the principal or supporting method...
Controlling rehabilitation training using patients' desired motion states is helpful to motivate their active participation, and further to improve training effect. Generally, motion states are recognized by applying EMG or biomechanics information, these methods have great limitations for the patients who lost important muscle groups or have weakened muscle functions. This paper proposed a method...
Previous research on sentiment classification by machine learning algorithms has shown that they usually work well with large-scale dataset. However, most open datasets for Chinese sentiment classification are quite small. In this paper we build a large-scale annotated Chinese sentiment dataset by filtering a vast amount of human-computer conversations. We conduct thorough experiments by using Convolutional...
One of the most critical issues facing solar plants is to ensure an efficient monitoring of installations, such as localizing dust or broken panels. Filming with robots or drones is widely used, but it is difficult to exploit directly the captured videos. In order to facilitate the monitoring task, we propose a technique to prepare a large panoramic image view of the desired area from the captured...
In object recognition techniques, specially feature-based methods, a fundamental step is to extract keypoints which are distinct and considerably interesting in the image. There are many different keypoint detectors already available, each with its own specific use and results vary enormously. It is widely agreed that evaluation of feature detectors is important. To our knowledge there is no comparative...
Feature extraction and classification algorithm is the key to classification accuracy. Terrain recognition for off-road robot need higher real-time classification algorithm, while the traditional neural network training method is difficult to meet the requirements. Extreme learning machine is used to classify the terrain pictures collected by robot in real time. Experimental results show that the...
In this paper we propose a method of extrinsically calibrating two of the most commonly used sensors in autonomous robotic systems: a 2-D lidar sensor and camera. Using a tri-planar calibration target, our method extracts rich point and planar feature information from the measurements of both sensors. We approach the problem of estimating the extrinsic paramaters using optimisation, and by minimising...
Robots often operate in built environments containing underlying structure that can be exploited to help predict future observations. In this work, we present a deep learning based approach to predict exit locations of buildings. This technique exploits the inherent structure of buildings to create a model. A convolutional neural network is trained using a database of building blueprints and used...
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...
This paper presents a spatial layout recovery approach from single omnidirectional images. Vertical structures in the scene are extracted via classification from heterogeneous features computed at the superpixel level. Vertical surfaces are further classified according to their main orientation by fusing oriented line features, floor-wall boundary features and histogram of oriented gradients (HOG)...
Social activity based on body motion is a key feature for non-verbal and physical behavior defined as function for communicative signal and social interaction between individuals. Social activity recognition is important to study human-human communication and also human-robot interaction. Based on that, this research has threefold goals: (1) recognition of social behavior (e.g. human-human interaction)...
A rail yard is a dangerous environment for humans to work in, primarily because of the possibility of serious injuries associated with moving rail cars, locomotives, and uneven terrain. For robots to act autonomously in such environments, there exists a need for a perception system that can act reliably under uncertain conditions. This uncertainty arises from multiple factors—uncontrolled lighting,...
Mobile service robots have the potential to improve the efficiency of fruit production in orchards. One of the key tasks that such robots must perform is traversing the rows. Many of the past implementations of row following in orchards have been developed for rows where the trees appear like walls on both sides. Another orchard structure that is used is the pergola, where a sparse array of trunks...
One of the main challenges of current person recognition techniques lies on difficulties of recognition in various poses. Recently, attention has been focused on using soft biometric information extracted from the human body to overcome the biometric recognition system's limitation in unconstrained environments. In this paper, we integrate the face and body information in a linear combination. We...
This paper proposes a novel, laser-based localization method for the autonomous mobile robot in transformer substations. Iterative closet point (ICP) algorithm has been widely used in current laser localization system for locating the mobile robot. However, after initialization, current localization system cannot finish positioning without human assistance. There is a growing interest in finding an...
Wireless capsule endoscopy (WCE) is the prime diagnostic modality for the small-bowel. It consists in a swallowable color camera that enables the visual detection and assessment of abnormalities, without patient discomfort. The localization of the capsule is currently performed in the 3D abdominal space using radiofrequency (RF) triangulation. However, this approach does not provide sufficient information...
In this paper, we introduce a novel framework which applies known image features combined with advanced linear image representations for weed recognition. Our proposed weed recognition framework, is based on state-of-the-the art object/image categorization methods exploiting enhanced performance using advanced encoding and machine learning algorithms. The resulting system can be applied in a variety...
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