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Adaptive Facial Deformable Models for Tracking (ADAManT)

用于跟踪的自适应面部变形模型 (ADAManT)

基本信息

批准号：
EP/L026813/1
负责人：
Stefanos Zafeiriou
金额：
$ 12.49万
依托单位：
Imperial College London
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2014
资助国家：
英国
起止时间：
2014 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FL026813%2F1
关键词：
Adaptive Facial Deformable Models Tracking

项目摘要

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.).

我们建议开发的方法自动构建的人特定的面部可变形模型的鲁棒跟踪面部运动在不受约束的视频（记录的“在野外”）。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，并且几乎可以在任意记录条件下工作。该项目中开发的技术预计将在许多不同的应用中产生巨大影响，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），在游戏和电影行业中捕捉面部动作，创建虚拟化身，仅举几例。ADAMant技术的新奇是多方面的。我们提出了第一个，强大的，歧视性的可变形的面部模型，可以定制，在一个增量的方式，使他们可以自动定制自己的人的脸使用图像序列在不受控制的记录条件下（室内和室外）。此外，我们建议建立并公开发布第一个注释的面部标志，面部视频数据库“在野外”。最后，我们的目标是使用该数据库作为第一次面部地标跟踪“野外”竞赛的基础，该竞赛将作为顶级视觉场地的卫星研讨会（如ICCV 2015）。作为概念验证，并专注于新的应用，ADAMant技术将应用于（1）面部标志跟踪，用于机器分析人们在舒适的家中（室内）观看的产品广告的行为，以及（2）面部标志跟踪，用于使用移动的设备（室外）录制的视频进行自动面部验证。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，实现对新商业模式的实质性变革影响并利用数字世界是主要挑战之一。由于人脸是许多科学学科和商业模式的核心，ADAManT项目提供的技术可以重塑现有的商业模式，使其变得更加高效，同时也可以创造新的商业模式。在EPSRC的ICT优先事项中，我们的研究与自主系统和机器人技术极其相关，因为它能够开发能够在不受约束的环境中理解人类行为的机器人（即，机器人伴侣的设计，机器人作为导游等）。