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Comparing an automated high-definition oblique camera system to rearseat-observers in a wildlife survey in Tsavo, Kenya: Taking multi-species aerial counts to the next level

In aerial wildlife counts, human observers often fail to detect animals. We conducted a multi-species sample count in Tsavo National Park, Kenya, with traditional rear-seat-observers (RSOs) and an automated ‘oblique-camera-count’ (OCC) imaging system to compare estimates of 23 wildlife species derived from these two survey methods. An aerial Total Count of elephant, buffalo and giraffe, conducted a month previously, provided a further comparison. In the Tsavo Core (9560 km2), which harbours 80% of Tsavo’s elephants, the OCC system acquired 81

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Cameras replace human observers in multi-species aerial counts in Murchison Falls, Uganda

Wildlife counts in Africa and elsewhere are often implemented using light aircraft with ‘rear-seat-observer’ (RSO) counting crews. Previous research has indicated that RSOs often fail to detect animals, and that population estimates are therefore biased. We conducted aerial wildlife surveys in Murchison Falls Protected Area, Uganda, in which we replaced RSOs with high-definition ‘oblique camera count’ (OCC) systems. The survey area comprises forests, woodlands and grasslands. Four counts were conducted in 2015–2016 using a systematic-reconnaissance-flight (SRF) strip-transect design. Camera inclination

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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 experts. We formulate the video summarization task as a tracking problem: frames in which giraffes are successfully tracked are presumed to be typical poses/behaviors and not included in the summary; whereas frames containing track initializations or terminations are presumed to be atypical events and are therefore included in the summary. To implement

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