Facial Deformable Models of Animals

虽然动物及其行为的自动监测对动物健康和福利领域非常重要，但为此目的开发计算工具却很少受到科学界的关注。除了对人类的情感价值外，动物对社会和经济也很重要，开发这样的工具将是一个重大的变革，对所有这些领域都有直接影响。为此，F.D.M.A.将开发用于检测和跟踪动物面部行为的新工具，特别是用于学习和将动物面部变形模型拟合到不受约束的图像/视频中。尽管检测和跟踪人脸的算法最近已被证明能够在一定程度上应对看不见的变化（例如姿势、表情、照明、背景和遮挡），但目前的解决方案尚未解决动物面部的更多变化。fda开始挑战目前最先进的面部对齐和跟踪方法，并开发学习和拟合算法，可以处理非常大的形状和外观变化，通常会在动物的面部遇到。据我们所知，计算机视觉社区在过去从未探索过这个问题。因为动物的面部在形状和外观以及姿势和表情上表现出更大程度的可变性，因此与之前对人脸的研究相比，这一研究要困难得多，也不同。食品药品监督管理局开发的工具将能够自动分析和理解动物的面部行为，这对动物的健康和福利越来越重要。加强动物健康和福利的潜在好处是巨大的；对动物、它们的主人、社会、公共卫生和经济。猫和狗是fda选择的两个物种，它们是世界上最受欢迎的伴侣动物，具有巨大的社会和经济重要性。据我们所知，计算机视觉在检测和跟踪图像和视频中动物的面部变形形状和运动方面还没有先验的工作。fda正着手开发这样的工具，以实现对动物面部行为的自动理解。除了动物健康和福利，食品药品监督管理局开发的计算机视觉工具还可以用于促进其他科学学科的研究，如动物行为、视觉和机器人。

Although the automatic monitoring of animals and their behaviour is of great importance to the field of animal health and welfare, developing computational tools for this purpose has received little attention by the scientific community. Aside the emotional value that they may have to people, animals are also important to the society and the economy, and developing such tools will be a big, transformative step with direct impact on all these areas. Towards this end, F.D.M.A. will develop novel tools for detecting and tracking animal facial behaviour, and in particular, for learning and fitting facial deformable models of animals to unconstrained images/video. Although algorithms for detecting and tracking of human faces have been recently shown capable of coping to some extent with unseen variations (e.g. pose, expression, illumination, background and occlusion), there is much more variability in the face of animals that the current solutions have not yet addressed. F.D.M.A. sets out to challenge the current state-of-the-art methods in face alignment and tracking, and develop learning and fitting algorithms that can deal with very large shape and appearance variations, typically encountered in animal faces. To the best of our knowledge, this problem has never been explored in the past by the Computer Vision community. It is significantly more difficult and different than prior work on human faces, as animal faces exhibit a much larger degree of variability in shape and appearance as well as in pose and expression.The tools to be developed by F.D.M.A. will enable the automatic analysis and understanding of animal facial behaviour which is of growing importance to animal health and welfare. The potential benefits of enhanced animal health and welfare are great; for animals, their owners, society, public health and the economy. Cats and dogs, the two species chosen by F.D.M.A., are the most popular companion animals, worldwide and of enormous societal and economic importance. To the best of our knowledge, there is no prior work in computer vision on detecting and tracking the facial deformable shape and motion of animals in images and videos. F.D.M.A. sets out to develop such tools that will enable automatic facial animal behaviour understanding. Aside animal health and welfare, the Computer Vision tools to be developed by F.D.M.A. can be used to facilitate research in other scientific disciplines, such as Animal Behaviour, Vision and Robotics.