This paper proposes a generic methodology for the semi-automatic generation of reliable
position annotations for evaluating multi-camera people-trackers on large video data sets.
Most of the annotation data are automatically computed, by estimating a consensus tracking
result from multiple existing trackers and people detectors and classifying it as either reliable
or not. A small subset of the data, composed of tracks with insufficient reliability, is verified by
a human using a simple binary decision task, a process faster than marking the correct …