Simultaneous positioning and identifying objects accurately and reliably is a fundamental problem in computer vision. General solutions to this problem is still challenging. For certain applications to achieve high accuracy and reliability in both tasks can be achieved if the objects can be labeled, e.g. multiple simultaneous robot tracking and navigation. We suggest a labeling technique using spiral patterns for optimal position estimation and identity recognition using the generalized structure tensor and tresholds. The technique adapts the synthesis of the labels to the frequency characteristics of the detection method. The approach has been implemented and tested by an over-head camera to track and control 8 robots in real-time.