Adaptive Facial Deformable Models for Tracking (ADAManT)

我们建议开发自动构建特定于人的面部变形模型的方法，以在不受限制的视频(在野外录制的)中稳健地跟踪面部运动。预计这些工具可以很好地处理像网络摄像头一样便宜的设备记录的数据，而且几乎可以在任意的记录条件下使用。预计该项目将开发的技术将对许多不同的应用产生巨大影响，包括但不限于生物识别(人脸识别)、人机交互(HCI)系统，以及使用面部信息(例如YouTube)对视频进行分析和索引、在游戏和电影行业捕获面部动作、创建虚拟化身等，仅举几例。坚固技术的新颖性是多方面的。我们提出了第一个稳健的、可辨别的可变形面部模型，可以以增量的方式进行定制，以便它们可以在不受控制的记录条件下(室内和室外)使用图像序列自动根据人的面部定制自己。此外，我们建议建立并公开发布第一个关于面部地标的注释面部视频数据库，该数据库是在野外制作的面部视频。最后，我们的目标是将该数据库用作第一届面部标志性跟踪比赛的基础，该比赛将作为顶级视觉场馆(如ICCV 2015)的卫星研讨会。作为概念证明，并将重点放在新的应用上，Adamant技术将被应用于(1)面部里程碑跟踪，以响应人们在家中(室内)舒适地观看产品广告时的机器行为分析，以及(2)面部里程碑跟踪，使用移动设备(室外)录制的视频进行自动人脸验证。在日益全球化的经济和无处不在的数字时代，市场可能会迅速变化。正如英国研究委员会的数字经济主题所规定的那样，实现对如何创造新的商业模式和利用数字世界的重大变革影响是主要挑战之一。由于人脸是许多科学学科和商业模式的核心，坚定不移的项目提供了可以重塑现有商业模式的技术，使其变得更有效率，同时也创造了新的商业模式。在EPSRC的ICT优先事项中，我们的研究与自主系统和机器人学极其相关，因为它使能够理解人类在不受限制的环境中的行为的机器人的开发成为可能(例如，机器人同伴的设计，机器人作为导游等)。

We propose to develop methodologies for automatic construction of person-specific facial deformable models for robust tracking of facial motion in unconstrained videos (recorded 'in-the-wild'). The tools are expected to work well for data recorded by a device as cheap as a web-cam and in almost arbitrary recording conditions. The technology that will be developed in the project is expected to have a huge impact in many different applications including but not limited to, biometrics (face recognition), Human Computer Interaction (HCI) systems, as well as, analysis and indexing of videos using facial information (e.g., YouTube), capturing of facial motion in games and film industry, creating virtual avatars, just to name a few. The novelty of the ADAMant technology is multi-faceted. We propose the very first, robust, discriminative deformable facial models that can be customized, in an incremental fashion, so that they can automatically tailor themselves to the person's face using image sequences under uncontrolled recording conditions (both indoors and outdoors). Also, we propose to build and publicly release the first annotated, with regards to facial landmarks, database of facial videos made 'in-the-wild'. Finally, we aim to use the database as the base of the first competition for facial landmark tracking 'in-the-wild', which will run as a satellite workshop of a top vision venue (such as ICCV 2015). As a proof of concept, and with a focus on a novel application, the ADAMant technology will be applied for (1) facial landmark tracking for machine analysis of behaviour in response to product adverts watched by people at comfort of their home (indoors) and (2) facial landmark tracking for automatic face verification using videos recorded by mobile devices (outdoors). In an increasingly global economy and ever-ubiquitous digital age, the market can change rapidly. As stipulated by the UK Researcher Councils' Digital Economy Theme, realising substantial transformational impact on how new business models are being created and taking advantage of the digital world is one of the main challenges. As human face is at the heart of many scientific disciplines and business models, the ADAManT project provides technology that can reshape established business models to become more efficient but also create new ones. Within EPSRC's ICT priorities our research is extremely relevant to autonomous systems and robotics, since it enables the development of robots capable of understanding human behaviour in unconstrained environments (i.e., design of robot companions, robots as tourist guide, etc.).