Efficient tracking using a robust motion estimation technique

Lalos, Constantinos; Voulodimos, Athanasios; Doulamis, Anastasios; Varvarigou, Theodora

doi:10.1007/s11042-012-0994-3

Cited by 19 publications

(6 citation statements)

References 33 publications

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“…Figure 5 depicts every frame as obtained by Kinect. Kinect permits capturing human motion variation as 3D data [15,32], combining the skeletal tracking data of multiple sensors to address the issue of occlusions [33] hence making skeletal tracking more robust. Kinect II sensor by Microsoft includes: (a) a depth sensor, (b) an RGB camera and (c) a four-microphone array that can deliver a full body 3D motion capture [7].…”

Section: Kinect Sensormentioning

confidence: 99%

Choreographic Pattern Analysis from Heterogeneous Motion Capture Systems Using Dynamic Time Warping

et al. 2019

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The convention for the safeguarding of Intangible Cultural Heritage (ICH) by UNESCO highlights the equal importance of intangible elements of cultural heritage to tangible ones. One of the most important domains of ICH is folkloric dances. A dance choreography is a time-varying 3D process (4D modelling), which includes dynamic co-interactions among different actors, emotional and style attributes, and supplementary elements, such as music tempo and costumes. Presently, research focuses on the use of depth acquisition sensors, to handle kinesiology issues. The extraction of skeleton data, in real time, contains a significant amount of information (data and metadata), allowing for various choreography-based analytics. In this paper, a trajectory interpretation method for Greek folkloric dances is presented. We focus on matching trajectories’ patterns, existing in a choreographic database, to new ones originating from different sensor types such as VICON and Kinect II. Then, a Dynamic Time Warping (DTW) algorithm is proposed to find out similarities/dissimilarities among the choreographic trajectories. The goal is to evaluate the performance of the low-cost Kinect II sensor for dance choreography compared to the accurate but of high-cost VICON-based choreographies. Experimental results on real-life dances are carried out to show the effectiveness of the proposed DTW methodology and the ability of Kinect II to localize dances in 3D space.

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Section: Kinect Sensormentioning

confidence: 99%

Choreographic Pattern Analysis from Heterogeneous Motion Capture Systems Using Dynamic Time Warping

et al. 2019

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“…The method to enable the tracking of actors is based on several studies [23][24][25]. This part of the implementation includes either the visual tracking of actors' movement on the stage or tracking, using Bluetooth technology, the location of wearable sensors attached to the actors' clothes.…”

Section: Tracking System Of Actorsmentioning

confidence: 99%

Designing a Virtual Reality Platform to Facilitate Augmented Theatrical Experiences Based on Auralization

Lakka

Malamos

Pavlakis

et al. 2019

Designs

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In the last few years, the immersive theater has become a new trend for modern performances. Venues increasingly utilize widely available computer technologies, such as virtual/augmented reality and spatial sound, to help facilitate the realization of different ideas. Motivated by this current trend, a prototype platform has been developed that enables the design and implementation of an augmented theatrical experience based on spatial sound immersion. This paper describes the implementation of the platform and, through several use case scenarios, its evaluation. The paper concludes with a discussion of the results and offers some thoughts on future developments.

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“…A significant application domain is automatic video surveillance, e.g., for safety, security, and quality assurance reasons. In this 5 Complexity experiment, we will make use of real-world video sequences from the surveillance camera of a major automobile manufacturer (NISSAN) [31], captured in the context of the SCOVIS EU project in the publicly available Workflow Recognition (WR) dataset [32].…”

Section: Activity Recognition From Video For Industrial Workflowmentioning

confidence: 99%

On the Impact of Labeled Sample Selection in Semisupervised Learning for Complex Visual Recognition Tasks

2018

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One of the most important aspects in semisupervised learning is training set creation among a limited amount of labeled data in such a way as to maximize the representational capability and efficacy of the learning framework. In this paper, we scrutinize the effectiveness of different labeled sample selection approaches for training set creation, to be used in semisupervised learning approaches for complex visual pattern recognition problems. We propose and explore a variety of combinatory sampling approaches that are based on sparse representative instances selection (SMRS), OPTICS algorithm, k-means clustering algorithm, and random selection. These approaches are explored in the context of four semisupervised learning techniques, i.e., graph-based approaches (harmonic functions and anchor graph), low-density separation, and smoothness-based multiple regressors, and evaluated in two real-world challenging computer vision applications: image-based concrete defect recognition on tunnel surfaces and video-based activity recognition for industrial workflow monitoring.

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Efficient tracking using a robust motion estimation technique

Cited by 19 publications

References 33 publications

Choreographic Pattern Analysis from Heterogeneous Motion Capture Systems Using Dynamic Time Warping

Choreographic Pattern Analysis from Heterogeneous Motion Capture Systems Using Dynamic Time Warping

Designing a Virtual Reality Platform to Facilitate Augmented Theatrical Experiences Based on Auralization

On the Impact of Labeled Sample Selection in Semisupervised Learning for Complex Visual Recognition Tasks

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