More advanced work on computer vision for animal identification, presented in the paper 'Automated identification of animal species in camera trap images' could perhaps be adapted for elephant detection.
In the method outlined in this paper, we have a flow of:
1. Animal images cropped out of background (overcoming cluttered background problems)
2. Sparse coding spatial pyramid matching (ScSPM) extracts dense SIFT (Scale-invariant feature transform) descriptor and cell-structed local binary patterns (cLBP) as the local features
3. Generation of global feature via weighted sparse coding and max pooling using multi-scale pyramid kernal
4. Classify images using a linear support vector machine algorithm