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Flyer is a means utilized popularly and effectively in recording landscape from above, collecting data of environment and weather, contributing to field works, especially conveying samples and medications from or to patients living in areas isolated by flood. It is necessary to track flyer's locations and characteristics for its activities. Visualization-based system for tracking flyer enables user...
Indoor positioning system is a rapidly emerging technology. Unlike outdoor positioning, which uses triangulation from satellites in line-of-sight, current indoor positioning methods attempt triangulation using Received Signal Strength Indicator (RSSI) from indoor transmitters, like WiFi and RFID. These methods, however, are not accurate and suffer from issues like multi-path and absorption by walls...
Currently, the understanding of the human mobility is an important challenge that has a large number of applications, especially in the study of a nation's ability to thrive economically and socially. Some works have shown that, it is possible to observe developed and developing countries reviewing their administrative regions borders, in order to reduce costs, or to solve ethnic claims and/or independence...
Action classification in videos has been a very active field of research over the past years. Human action classification is a research field with application to various areas such as video indexing, surveillance, human-computer interfaces, among others. In this paper, we propose a strategy based on decreasing the number of features in order to improve accuracy in the human action classification task...
The purpose of Detect and Avoid (DAA) is to maintain Well Clear between ownship and any potential intruders. One sub-function of a DAA system is the human interface where aural alerts and visual guidance for maintaining Well Clear are displayed to the pilot. However, situations can occur where Well Clear is lost. In such situations, the visual guidance must change from displaying guidance meant to...
Navigation and mapping in relatively featureless underwater and under-ice environments is a difficult challenge. Using common sensors already onboard many unmanned underwater vehicles to aid in this process provides a self-contained and cost-effective solution. Evaluation of such visual navigation and mapping methods under development requires multiple UUVs to gather the required sonar and video data...
The paper presents a method for developing illusionary flight profiles situations for practical testing of pilots using the GYRO IPT II spatial disorientation simulator. Standard flight profiles do not use the full capability of the simulator to train pilots for recognition and recovery from illusions appearing unexpectedly. For this reason, there is a need to create new flight profiles so as to demonstrate...
In discovering nature of the Primary Language of the human brain introduced by J. von Neumann, we suggest that the Primary Language is the Language of Visual Streams. We investigate the Primary Language by researching major ancient algorithms that have been developed as a result of evolution of human intelligence and should be based directly on the Primary Language. One of them is the Algorithm of...
Action recognition has been one of the most popular fields of computer vision. This paper presents a novel approach to action recognition problem using the dimension reduction method, local fisher discriminant analysis, to reduce the dimension of feature descriptors as the preprocessing step after feature extraction. We propose to use sparse matrix and randomized kd-tree to modify and accelerate the...
The area outside our central field of vision, also referred to as the visual periphery, captures most information in a visual scene, although much less sensitive than the central Fovea. Vision studies in the past have stated that there is reduced sensitivity of texture, color, motion and flicker (temporal harmonic) perception in this area, that bears an interesting application in the domain of quality...
In this paper we propose to improve the localization and the 3D mapping provided by an RGBD SLAM algorithm, using a prior knowledge of the 3D model of the environment. The proposed solution relies on an feature-based RGBD SLAM algorithm to localize the camera and update the 3D map of the scene. To improve the accuracy and the robustness of the localization, we propose to combine in a local bundle...
Action recognition has been one of the challenging problems in the computer vision community. Most of the recent research work in this area exploits the motion features captured by dense trajectory descriptors. On the other hand, static image classification has seen the rise of deep learning architectures, with evidence that the output of intermediate layers could be successfully employed as a low...
We present a novel video representation for human action recognition by considering temporal sequences of visual words. Based on state-of-the-art dense trajectories, we introduce temporal bundles of dominant, that is most frequent, visual words. These are employed to construct a complementary action representation of ordered dominant visual word sequences, that additionally incorporates fine grained...
In contrast to still image analysis, motion information offers a powerful means to analyze video. In particular, motion trajectories determined from keypoints have become very popular in recent years for a variety of video analysis tasks, including search, retrieval and classification. Additionally, cloud-based analysis of media content has been gaining momentum, so efficient communication of salient...
This study aims to propose a system to visualize the velocity of motion, velocity/change of acceleration, and shape of trajectory based on the information measured by optical motion capture systems. It is difficult to figure out the above-mentioned information only by physical movements. The system uses various sizes of spheres and trigonal pyramids as well as colors and line segments to express velocity...
Despite the huge research on crowd on behavior understanding in visual surveillance community, lack of publicly available realistic datasets for evaluating crowd behavioral interaction led not to have a fair common test bed for researchers to compare the strength of their methods in the real scenarios. This work presents a novel crowd dataset contains around 45,000 video clips which annotated by one...
This paper discusses the problem of one shot gesture recognition. This is relevant to the field of human-robot interaction, where the user's intentions are indicated through spontaneous gesturing (one shot) to the robot. The novelty of this work consists of learning the process that leads to the creation of a gesture, rather on the gesture itself. In our case, the context involves the way in which...
The discovery of anomalies and, more in general, of events of interest at sea is one of the main challenges of Maritime Situational Awareness. This paper introduces an event-based methodology for knowledge discovery without querying directly a large volume of raw data. The proposed architecture analyses the maritime traffic data to detect maritime traffic patterns and events and aggregate them in...
We address the problem of modeling complex target behavior using a stochastic model that integrates object dynamics, statistics gathered from the environment and semantic knowledge about the scene. The method exploits prior knowledge to build point-wise polar histograms that provide the ability to forecast target motion to the most likely paths. Physical constraints are included in the model through...
A video contains rich perceptual information, such as visual appearance, motion and audio, which can be used for understanding the activities in videos. Recent works have shown the combination of appearance (spatial) and motion (temporal) clues can significantly improve human action recognition performance in videos. To further explore the multimodal representation of video in action recognition,...
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