Paper Info
Title
Supporting activity recognition by visual analytics
Abstract
Recognizing activities has become increasingly relevant in many application domains, such as security or ambient assisted living. To handle different scenarios, the underlying automated algorithms are configured using multiple input parameters. However, the influence and interplay of these parameters is often not clear, making exhaustive evaluations necessary. On this account, we propose a visual analytics approach to supporting users in understanding the complex relationships among parameters, recognized activities, and associated accuracies. First, representative parameter settings are determined. Then, the respective output is computed and statistically analyzed to assess parameters' influence in general. Finally, visualizing the parameter settings along with the activities provides overview and allows to investigate the computed results in detail. Coordinated interaction helps to explore dependencies, compare different settings, and examine individual activities. By integrating automated, visual, and interactive means users can select parameter values that meet desired quality criteria. We demonstrate the application of our solution in a use case with realistic complexity, involving a study of human protagonists in daily living with respect to hundreds of parameter settings.
Year
DOI
Venue
2015
10.1109/VAST.2015.7347629
2015 IEEE Conference on Visual Analytics Science and Technology (VAST)
Keywords
DocType
Citations 
I.3.6 [Computing Methodologies]: Computer Graphics—Methodology and Techniques,H.5.2 [Information Interfaces and Presentation]: User Interfaces—Theory and methods
Conference
0
PageRank 
References 
Authors
0.34
15
8
Name
Order
Citations
PageRank
martin rohlig1136.32
Martin Luboschik2455.83
Frank Krüger300.34
Thomas Kirste411725.44
Heidi Schumann51691122.34
Markus Bögl6423.78
Bilal Alsallakh719611.71
Silvia Miksch82212174.85