Tracking Multiple-person using Sparse Stereo Information

Multiple-Person Tracking for a Mobile Robot Using Stereo

This paper describes a method of detecting and tracking two or more persons from images captured with a moving camera. We propose a method of person tracking using distance information calculated with a stereo camera. Each person’s position is estimated by using Kalman filter in consideration of movement of a mobile robot and persons. Additionally, we report an experimental result on control of...

Multi-Person Tracking with Stereo Range Sensors

Motivation: Systems which can track and understand people have a wide variety of commercial applications. It is predicted that computers of the future will interact more naturally with humans than they do now. Instead of the desktop computer paradigm with humans communicating by typing, computers of the future will be able to understand human speech and movements. Our system demonstrates the ca...

Improving Appearance-based 3d Face Tracking Using Sparse Stereo Data

Recently, researchers proposed deterministic and statistical appearance-based 3D head tracking methods which can successfully tackle the image variability and drift problems. However, appearance-based methods dedicated to 3D head tracking may suffer from inaccuracies since these methods are not very sensitive to out-of-plane motion variations. On the other hand, the use of dense 3D facial data ...

Generation of 3D Sparse Feature Models Using Multiple Stereo Views

Head Tracking Using Stereo

A different perspective to head tracking, one of the more studied topics in computer vision is presented here. The heavy reliance of contemporary head trackers on intensity images is countered here. The algorithm presented here, uses stereo data to track the head of a moving subject. This is used to achieve effective and accurate foreground segmentation. The head is modeled as an ellipse and tr...