Comments (1)
SPENCER was a EU project (finished in 2016) with the aim of developing algorithms for service robots that can guide groups of people through highly dynamic and crowded pedestrian environments.
The people tracker developed within this project includes the following steps:
- motion prediction: for each detected person, motion is predicted using an Extended Kalman filter. To deal with dynamic environments, a bank of first and second order motion models is used and combined in an Interacting Multiple Models filter (IMM);
- data association: new incoming detections are associated with existing tracks using the Nearest-Neighbor (NN), which selects the track minimizing the distance between detection and prediction;
A track initiation logic is also included, which confirms a set of detections to be a track if:
- its speed is restricted to a pre-defined interval
[v_min,v_max]
- the Euclidean distance between the current detection and the prediction of the track candidate is below a threshold.
This video shows the result of the tracking on a mobile platform in a real crowded environment (airport). The scenario is rather complex, extremely dynamic and the tracker seems to work well (note: detections are obtained with both RGB-D sensors and 2D laser range sensors), with low CPU consumption (less than 10% of a single i7 Core).
We might rely on a similar strategy for dealing with distractors (in the case of 6MWT, people not relevant for the test can walk throughout the corridor). From our previous analysis (#171), data appear consistent to apply a NN strategy.
from assistive-rehab.
Related Issues (20)
- Remember to update CI for VCPKG Ports name HOT 1
- Update YARP portmonitor initialization HOT 5
- Use `depthimage_compression_zlib` pormonitor HOT 1
- Dependencies for cornerRefinementMethod HOT 2
- `lineDetector` and `skeletonRetriever` are to rely on I/F to get depth camera's params HOT 2
- CI fails because of `curl` build error HOT 4
- Setup and test the TUG demo on R1SN003 HOT 41
- Develop the connection Navigation ➡️ GRACE HOT 2
- Refine and test speech failure detection on R1SN003
- Host docker images on `ghcr.io/robotology` HOT 3
- Update kinematics for use with top camera
- Test the TUG metrics accuracy with and without human planes projection HOT 3
- Expose the available TUG metrics to the end user HOT 8
- Investigate the possibility to replace the Wi-Fi buttons HOT 3
- General upgrades to assistive-rehab docker image HOT 1
- Release `v0.8.0`
- Update website
- Improve the peak finding algorithm for gait estimation HOT 5
- Investigate possible race condition in `googleSpeech` module
- Improve handling of questions by `managerTUG` HOT 4
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from assistive-rehab.