Monitoring Giraffe Behavior in Thermal Video

We present a solution for monitoring nocturnal giraffe behavior by reducing several hours of thermal camera surveillance footage into a short video summary which can be reviewed by human analysts. We formulate the video summarization task as a tracking problem: frames in which giraffes are tracked are presumed to be typical poses/behaviors and not included in the summary, whereas frames where tracks initialize or terminate are presumed to be atypical events and are therefore included in the summary. To implement our tracking-by-detection summarization approach, we explore various combinations of image features for long wave infrared spectrum cameras, and devise a parts-based object detection technique using geodesic distances to handle the extreme variations of typical giraffe postures. Finally, we evaluate our summarization performance in terms of recall and compressibility, and show how a trade-off exists between these two measures using more fragile or robust tracking techniques.