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Crowd behaviour analytics focuses on behavioural characteristics of groups of people instead of individuals' activities. This work considers human queuing behaviour which is a specific crowd behavior of groups. We design a plug-and-play system solution to the queue detection problem based on Wi-Fi/Bluetooth Low Energy (BLE) received signal strength indicators (RSSIs) captured by multiple signal sniffers...
Object recognition the is an important step for the high-level visions processing tasks, such as security managing, and abnormality event analysis. In this paper, we address these challenges of abnormal water surface monitoring in real-world unconstrained environments where the background is complex and dynamic. In the algorithm proposed, firstly we extract the Gaussian-Hermite moment features of...
This paper presents a natural corners-based two-dimensional (2D) Simultaneous Localization and Mapping (SLAM) with a robust data association algorithm in a real unknown environment. The corners are extracted from raw laser sensor data and chosen as landmarks for correcting the pose of mobile robot and building the map. In the proposed data association method, the extracted corners in every step are...
This paper proposes the occlusion avoidance method in comers-based simultaneous localization and mapping (SLAM) with different data association algorithms. The redundant or wrong features are extracted if part of the object is occluded. The comers are chosen by intersecting two adjacent line segments and selecting the end-points of some special line segment. When two segments are far enough, the nearest...
This paper presents a 3D point cloud map construction method based on extracted line segments with two mutually-perpendicular laser sensors in unknown indoor environment. To correct the position of mobile robot, the line segments are extracted from the raw sensor data from a horizontally installed laser sensor. In each step, these extracted segments are chosen as landmarks and matched with the stored...
The algorithm of line extraction and corner extraction in unknown indoor environment with laser sensor is presented in this paper. The corners, the intersection point of two line segments and the two endpoints of each line segment extracted from raw sensor data, can be chosen as landmarks to estimate the position of mobile robot or used to do mapping unknown environment without artificial landmarks...
Most existing feature selection methods focus on ranking features based on an information criterion to select the best K features. However, several authors have found that the optimal feature combinations do not give the best classification performance [8],[7]. The reason for this is that although an individual feature may have limited relevance to a particular class, when taken in combination with...
For overcoming defect of vector-based nondynamic and parameter specifies method which based on linear transformation feature extraction, a iris feature extraction method which based on the Independent Component Analysis (ICA) is advanced. This method almost removed redundancy of feature space and overcome the defect of traditional linear transformation feature-based vectors non-dynamic. And then Self-Organizing...
According to the visible characteristics of speech, a new speech recognition system design was proposed. It based on multiple neural networks. Firstly, Pulse Coupled Neural Network(PCNN) was input into the spectrogram for producing the corresponding time series icon as the feature parameters of speech. And then, the feature parameters was input into the Probabilistic Neural Networks(PNN) for training...
Moments are widely used in pattern recognition, image processing, computer vision and multi resolution analysis. In this paper, we first printout Gaussian-Hermite moments, and propose a new method to extract the character features based on Gaussian-Hermite moments. Following, for training network, the moment features were inputted to BP network as the parameters; so that, a classifier was realized...
In this paper, we show how to extract gender discriminating features from 2.5D facial needle-maps. The standard eigenspace analysis method for non-Euclidean data is principal geodesic analysis (PGA). Based on PGA, we propose a novel supervised weighted PGA method which incorporates local weights into standard PGA to improve gender discriminating capability of the extracted features. The weight map...
In this paper, we address these challenges in real-world unconstrained environments where the background is complex and dynamic. In the algorithm proposed, we extract the features in a color space, accumulate the feature information over a short time, and fuse high-level knowledge and low-level feature information. A fuzzy technique is also developed to detach silhouettes of moving objects from a...
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