Computer Vision for Wildlife Conservation (CVWC)Oct-27, 2019 @ Room-327A, COEX Convention Center, Seoul, Korea
Conservation of wildlife is important to maintaining a healthy and balanced ecosystem, and ensuring the continued biodiversity of our world. In particular,endangered species serve as an important indicator for biodiversity and environmental health. Governments around the world along with environmental organizations such as WWF (World Wildlife Fund) have dedicated many resources and projects to protect endangered species.
Critical to wildlife conservation is monitoring trends in the geospatial distribution of wildlife, and tracking population. This foundational data guides resourcing and strategies for wildlife protection, and potentially alert for situational changes that impact endangered species. Growing challenges such as wide range of activity, poaching, loss of habitat, and others have made tracking wildlife an increasingly difficult task. Fortunately, computer vision techniques have shown promises in addressing several of these challenges, since we are now able to collecting plenty of imagery data from camera trap or even UAVs, and use this imagery to build edge-to-cloud systems for wildlife conservation. From the edge deployment perspective, CV techniques can be applied to smart imaging sensors to capture wildlife related images/video and monitor wildlife. Because cloud systems have access to significantly more compute, we can apply more sophisticated tasks such as re-identifying certain wildlife individuals from a large amount of photos from distributed cameras, tracking movement patterns, and aggregating population information across multiple sensors.
This workshop aims to enhance the social responsibility of the CV community, and bring together researchers in the community to advance wildlife conservation using CV techniques from 3 aspects:
- Welcome contributed papers in a broad area of CV for wildlife conservation.
- Organize a challenge on dataset we collected for Amur tiger conservation with tasks like tiger detection, pose estimation and re-identification.
- Foster new ideas and directions on "CV for wildlife conservation" with invited talks and panel discussions from both the CV community and traditional wildlife conservation community.