## 2 Materials and Methods
### Experimental Design for Human CT Images  
We conducted the human CT experiments between 13-19 March 2020 (see Institutional Review Board Statement). We used two Bushnell Trophy Cam HD Aggressor 2017 (model number: 119877, Bushnell, Overland Park, KS, USA) CTs to collect data. We also varied the following factors during the experiments: clothing colour, time-of-day, the distance between the human and CT, occlusion, the orientation of the human relative to the CT, and human height, with naturally varying tree density. A total of 15 human participants were involved, a mixture of LJMU students and local staff, who provided prior and informed consent. Each experiment varied in participant count, between two and six, depending on availability. Both green and blue coats and trousers were used interchangeably by each participant during the experiment, resulting in a completely blue and green set of clothing for each participant for each time-of-day, condition, and distance. There was a total of 11 daylight experiments (between 7:15-8:00) and 11 dusk experiments (between 19:15-20:00) within the miombo woodland (low tree density). The riverine forest (high tree density) experiments were conducted consecutively on 19 March 2020 (between 10:00-15:00), resulting in six daylight experiments. For the daylight experiments, participants walked from right-left horizontally (relative to the CT) across the 5-m marker. Once participants reached the end, they walked up the side of the experiment field (out of the CTs field of view) to the left-hand side of the 10-m marker and walked left-right across the 10-m distance. They continued this pattern across each set distance, starting at 5 m up to 30 m; once completed, participants returned to the centre of the 30-m distance marker and walked through the centre, directly towards the CT (see Appendix A Figure A1 for a visual representation). For the dusk experiments, we randomly allocated participants a specific distance to walk across to the end and return to their starting position (see Appendix A Figure A2 for a visual representation). We used a 5-m tape measure to measure the distance from the CT using 5-m intervals (<5, 5, 10, 15, 20, 25, and 30 m) and marked each distance using a fallen branch (central to the CT). The <5 m class included all images taken of participants, between the CT and 5-m distance marker, excluding dusk CT experiments. Next, we measured the CTs field of view by using a live feed video and having an individual walk across each set distance marker and stop once their body left the side of the CTs field of view; the individual then placed a stick on the ground as the perimeter marker. We did this at both ends of each set distance marker. Afterwards, we measured the distance between the left and right markers for each distance class and used these measurements as reference points for additional experiments. Proceeding this, we replaced the fallen branch marking each distance class with yarn, tying it to the left and right perimeter markers, repeating for each distance class, enabling the participants to follow the yarn to the end of the marker. We then tested participant height variations, ranging between 1.5-1.9 m, using a 5-m tape measure. Once we captured the footage, we first measured target occlusion from the CT in classes (0-33%, 34-67%, and 68-100%). We used the following rule to identify occlusion--target occlusion occurs if any part of the body is not visible in the image, either due to obstruction of an object or the CTs field of view. We proceeded to measure the factor orientation towards the CT by selecting footage of the target moving or facing in the CTs direction. We then selected and organised the footage of humans orientated towards the CT into each set distance marker category. This included selecting footage captured at the following distance markers (<5, 5, 10, 15, 20, 25, and 30 m). We also associated all measured factors with their appropriate classification labels (see Table 1 for classification label overview).