1 Challenge the future

Efficient Navigation in Temporal,

Multi-Dimensional Point Sets Efficiёnte navigatie in tijd-afhankelijke, multi-dimensionale

puntengegevens

Christian Kehl

2 Challenge the future

General Introduction

• Plenty of point set scans available

• Many Application Areas

• Home Entertainment

• Construction Management

• Disaster Management

3 Challenge the future

General Introduction

• Problem 4D data: technical limitations of rendering system

• user‘s interests hard to find by traversing time-series data sets

• Goal: Visualisation algorithms for supportive user navigation

• Approaches:

• real-time rendered data traversal

• user-centred browsing

• navigation via visual summaries

Rendering & Navigation

Delfland dataset 1 time step 12.5 km * 10 km takes up to 3 hours to inspect in detail

User Interest: (top) Landslide

probability; (right) Door Surveillance

4 Challenge the future

Research Statement

“I will search for algorithms and scalable representations that allow for

interaction, queries, and exploration of time-dependent point data .”

5 Challenge the future

Subtopics

1. Scalable Rendering and Visualisation of time-dependent

Point Sets

2. Efficiently Browsing through time-dependent Datasets

3. Navigation by Visual Summaries

6 Challenge the future

Scalable Rendering and Visualisation of

time-dependent Point Sets

• Interactive Rendering of large point sets already demanding

• additional, time-related challenges:

• just developing branch, virtually no data sets openly available

=> no available rendering approaches

• Rendering of multiple time steps faces technical challenges

3Di project: currently

more than 12TB and growing

7 Challenge the future

Scalable Rendering and Visualisation of

time-dependent Point Sets

• Goal: efficient rendering system

• displays massive point sets

• multiple time steps at the same time

• exploits visual and technical limitations

• Contribution:

• time-dependent LoD technique by continuous refinement

• temporal caching of point sets

8 Challenge the future

Subtopics

1. Scalable Rendering and Visualisation of time-dependent

Point Sets

2. Efficiently Browsing through time-dependent Datasets

3. Navigation by Visual Summaries

9 Challenge the future

Efficiently browsing through time-

dependent datasets

• Use Case: Surveillance of restricted areas

-> user-defined monitoring of areas

• Use Case: Natural Disaster Monitoring

-> changing demands and interests, depending on zoom level

10 Challenge the future

Efficiently browsing through

time-dependent datasets

Problems:

• browse while only showing user-specific interest

• remove/hide redundant data

• selection and interactive exploration of temporal data

• handling varying user interests according to user viewpoint

11 Challenge the future

Efficiently browsing through time-

dependent datasets

Goal: Exploring navigation techniques

• user-centred interaction

• visual querying

• Level-of-Abstraction

12 Challenge the future

Subtopics

1. Scalable Rendering and Visualisation of time-dependent

Point Sets

2. Efficiently Browsing through time-dependent Datasets

3. Navigation by Visual Summaries

13 Challenge the future

Navigation by Visual Summaries

• “Visual Summary”: visual and effective way to summarize

complex datasets

• various applications in entertainment, construction etc.

Creation

14 Challenge the future

Navigation by Visual Summaries

• party in Kinect-supervised house

• lots of objects (people) -> lots of events and interests

• goal: summarize the party to re-live it another day

Creation - Entertainment

15 Challenge the future

Navigation by Visual Summaries

• construction of building demands experts of different fields

• time constraints prevent meetings at construction site

• goal: summarize recent construction events for remote

planning

Creation – Construction

16 Challenge the future

Navigation by Visual Summaries

Problems:

• suitable representations

• spatio-temporal incoherence

• events wide-spread in space and time across the dataset

• suitable guidance to important events in the dataset

18 Challenge the future

Navigation by Visual Summaries

• user-driven interconnection to group objects of different steps

• intuitive user interface to regulate amount of spatial- and

temporal coherence

• test visual representations to determine the most suitable one

• compound visual summary as an album of impressions

Approach - Entertainment example

19 Challenge the future

Navigation by Visual Summaries

• focus on Guidance along events

• visual 4D tour

• 4D scene capture as interactive representation of a summary

Approach – Construction Example

20 Challenge the future

Conclusion

• focus: Visually navigating efficiently in time-dependent, multi-

dimensional, scanned data

• applications:

• Efficient Visual Surveillance

• Disaster Assessment with dynamically changing user interests

• Home Entertainment: Re-live a 3D-recorded party another day

• Visually guide construction processes

21 Challenge the future

Conclusion

• Necessary techniques:

• Real-time Rendering of Datasets

• Efficient Browsing through Datasets according to user interests

• Visual Summaries and their use as Guidance Method in Datasets

22 Challenge the future

The following 3 months

• finish paper “Interactive Rendering of Large-Scale, Geospatial

Data“ (PROM-4 Scientific Writing)

• generate artificial, temporal test dataset

Time-dependent Level-of-Detail technique by continuous refinement

• Construct tree structure via spatial subdivision

• Tree node refers to a list of time steps

• Each time-step stores hierarchical LoD tree

• low-resolution height maps or volumes per cell

• On traversal – continuous refinement:

• morph previously loaded points by rough estimate

• replace them gradually by newly loaded points

Height Difference f(t-1, t)