Toward color image segmentation in analog VLSI: algorithm and hardware
International Journal of Computer Vision
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Mathematical Introduction to Robotic Manipulation
A Mathematical Introduction to Robotic Manipulation
Motion and Structure from Image Sequences
Motion and Structure from Image Sequences
W4S: A real-time system detecting and tracking people in 2 1/2D
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Cardboard People: A Parameterized Model of Articulated Image Motion
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Understanding Purposeful Human Motion
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Tracking of Persons in Monocular Image Sequences
NAM '97 Proceedings of the 1997 IEEE Workshop on Motion of Non-Rigid and Articulated Objects (NAM '97)
Estimation of Articulated Motion Using Kinematically Constrained Mixture Densities
NAM '97 Proceedings of the 1997 IEEE Workshop on Motion of Non-Rigid and Articulated Objects (NAM '97)
| Hi-index | 0.00 |
Within a human motion analysis system, body parts are modeled by simple virtual 3D rigid objects. Its position and orientation parameters at frame t+1 are estimated based on the parameters at frame t and the image intensity variation from frame t to t + 1, under kinematic constraints. A genetic algorithm calculates the 3D parameters that make a goal function that measures the intensity change minimum. The goal function is robust, so that outliers located especially near the virtual object projection borders have less effect on the estimation. Since the object's parameters are relative to the reference system, they are the same from different cameras, so more cameras are easily added, increasing the constraints over the same number of variables. Several successful experiments are presented for an arm motion and a leg motion from two and three cameras.