Object Detection and Recognition in Active Video

物体检测和识别定位视觉对象，识别其在图像和视频中的对应类别、身份和活动。该任务是理解图像和视频内容的基础，因此它是计算机视觉和多媒体的中心课题之一。一般来说，人类拍摄的数字视频是有目的的——瞄准感兴趣的对象（OOI）。典型的例子包括拍摄，专业的视频摄影师报道体育赛事，或在旅游景点（如建筑物，雕塑/雕像，人群/人的活动）的业余拍摄。努力定位OOI，通过特写或多个视图仔细检查它，并在它移动时跟踪它。我们称这样产生的视频为活动视频。它的特点是存在显著的OOI，有目的的摄像机运动产生更丰富的背景，并且比非活动视频更以对象为中心。******提出的研究计划的短期目标是为主动视频中视觉目标检测和识别的重要问题寻求新的答案。具体而言，该计划将研究和开发：(a)探索主动视频中的显著性和注意力模型的算法；(b)能够更好地反映活动环境的特征和描述符；(c)增强的分类器更具判别性、鲁棒性和效率。将开展几个应用领域的研究项目，包括，例如，3D有源视频和有源视频中的人脸。我研究的长期目标是推进基于视觉对象的图像和视频处理与分析的知识。它在很大程度上是由来自人类智能视觉系统的线索所驱动的。******这项研究的预期影响是双重的：(a)它将产生新的算法和解决方案，以更好地检测和识别视觉物体，这是数字视频和多媒体研究界和工业界迫切需要的。(b)它将以在顶级会议和期刊上发表学术论文的形式，直接促进这一领域知识的发现，并为加拿大培训高素质人才

Object detection and recognition localize visual objects and recognize their corresponding classes, identities, and activities in images and videos. This task is the foundation of understanding the image and video content, thus it is one of the central topics in Computer Vision and Multimedia. In general, digital video taken by humans is purposive -- aiming for the Object(s) of Interest (OOI). Typical examples include filming, professional video cameramen covering sporting events, or an amateur shooting at a tourist scene (e.g., buildings, sculptures/statues, and activities of the crowd/people). Efforts are made to locate the OOI, examine it closely by close-ups or multiple views, and follow it if it is moving. We call the video thus produced Active Video. It is characterized by the presence of salient OOI, richer context yielded by the purposive camera movements, and it is more object-centered than in non-active videos.******The short-term objectives of the proposed research program are to seek new answers to the important problem of visual object detection and recognition in Active Video. In particular, the program will research and develop: (a) Algorithms to explore saliency and attention models in Active Video; (b) Features and descriptors that can better capture the Active Context; and (c) Boosted classifiers that are more discriminative, robust, and efficient. Research projects in several application areas will be conducted including, for example, 3D Active Video and Faces in Active Video. The long-term objective of my research is to advance the knowledge in visual object-based image and video processing and analysis. It is largely motivated by cues from the intelligent human vision system.******The anticipated impact of this research is two-fold: (a) It will generate new algorithms and solutions for better visual object detection and recognition which are urgently needed by the digital video and multimedia research community and industries. (b) It will directly contribute to the discovery of knowledge in this area in the form of academic publications in top conferences and journals, and to the training of Highly Qualified Personnel (HQP) for Canada.**