TY - JOUR
AU1 - Regensburger, Uwe
AB - Object recognition is necessary for any mobile robot operating autonomously in the real world. This paper discusses an object classifier based on a 2-D object model. Obstacle candidates are tracked and analyzed false alarms generated by the object detector are recognized and rejected. The methods have been implemented on a multi-processor system and tested in real-world experiments. They work reliably under favorable conditions but sometimes problems occur e. g. when objects contain many features (edges) or move in front of structured background.
TI - Object classification for obstacle avoidance
JF - Proceedings of SPIE
DO - 10.1117/12.25460
DA - 1991-03-01
UR - https://www.deepdyve.com/lp/spie/object-classification-for-obstacle-avoidance-F0c0OSdSfB
SP - 112
EP - 119
VL - 1388
IS - 1
DP - DeepDyve
ER -