Video Based Tracking and Optimization Using Mean-Shift, Kalman Filter and Swarm Intelligence

Kulkarni, Ashvini; Vargantwar, Manasi; Virulkar, Sujata

doi:10.1109/iccubea.2015.129

Cited by 2 publications

(1 citation statement)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The performance of the tracking method using only one type of target representation is easily influenced by environmental noise including illumination changes, image blur, or camera movements. To improve the tracking performance, in this paper, a hybrid tracking technique is employed by combing the Hue Saturation Value (HSV) color feature, Mean Shift algorithm (Cheng, 1995) and Kalman filter (Kulkarni & Vargantwar, 2014). More precisely, the HSV color feature is employed to describe colors in terms of their shade and brightness.…”

Section: Methodsmentioning

confidence: 99%

Mining video data

Thompson,

Howard,

Yang

et al. 2016

APUBS

View full text Add to dashboard Cite

Learning spaces influence how we act, however there is a lack of systemic research addressing the impact of environments on teaching and learning. In this paper, we introduce a hybrid tracking technique in which a colour model is combined with algorithms to identify human positions, and applied to video data. The aim of identifying patterns of movement that could be used to indicate successful collaboration in open plan learning spaces. We apply the method to a previously analyzed dataset, to demonstrate how multiple analytic techniques can be used to build a complex understanding of learner movement in relation to collaboration and learning. We conclude with suggestions of the ways in which the results could be used by instructors to inform orchestration of complex learning environments, as well as directions for future research.

show abstract

Section: Methodsmentioning

confidence: 99%

Mining video data

Thompson,

Howard,

Yang

et al. 2016

APUBS

View full text Add to dashboard Cite

show abstract

Using Gamification and Mixed Reality Visualization to Improve Conceptual Understanding in ICT System Analysis and Design

Muñoz,

Cowling,

Birt

2016

APUBS

View full text Add to dashboard Cite

This paper presents a research design and intervention that investigates how the use of mixed reality visualization and gamification can be applied to an ICT systems analysis and design course. The research focuses on a learning approach of an ICT modelling and design framework based on visual augmentation of traditional course content and class delivery. Assessment of the learning impact in regards to learners, system components and their interaction in system scenarios will be performed. Allowing learners to explore and discover information in the form of a gamified scavenger hunt that supports scaffolding learning chunks, aims to assist them towards a conceptual understanding of the solution. Educators can incorporate selected representations of key learning artefacts and resources in an augmented capacity using a variety of media such as 2d images, videos, graphics, simulations, and 3d models applied into the design process and promote active learning in the classroom.

show abstract

Video Based Tracking and Optimization Using Mean-Shift, Kalman Filter and Swarm Intelligence

Cited by 2 publications

References 7 publications

Mining video data

Mining video data

Using Gamification and Mixed Reality Visualization to Improve Conceptual Understanding in ICT System Analysis and Design

Contact Info

Product

Resources

About