A worldwide movement in advanced manufacturing countries is seeking to reinvigorate (and revolutionize) the industrial and manufacturing core competencies with the use of the latest advances in information and communications technology. Visual computing plays an important role as the "glue factor" in complete solutions. This article positions visual computing in its intrinsic crucial role for Industrie 4.0 and provides a general, broad overview and points out specific directions and scenarios for future research.

One of the main challenges for the implementation of artificial intelligence (AI) in agriculture includes the low replicability and the corresponding difficulty in systematic data gathering, as no two fields are exactly alike. Therefore, the comparison of several pilot experiments in different fields, weather conditions and farming techniques enhances the collective knowledge. Thus, this work provides a summary of the most recent research activities in the form of research projects implemented and validated by the authors in several European countries, with the objective of presenting the already achieved results, the current investigations and the still open technical challenges. As an overall conclusion, it can be mentioned that even though in their primary stages in some cases, AI technologies improve decision support at farm level, monitoring conditions and optimizing production to allow farmers to apply the optimal number of inputs for each crop, thereby boosting yields and reducing water use and greenhouse gas emissions. Future extensions of this work will include new concepts based on autonomous and intelligent robots for plant and soil sample retrieval, and effective livestock management.

An overview of 3D and free viewpoint video is given in this paper with special focus on related standardization activities in MPEG. Free viewpoint video allows the user to freely navigate within real world visual scenes, as known from virtual worlds in computer graphics. Examples are shown, highlighting standards conform realization using MPEG-4. Then the principles of 3D video are introduced providing the user with a 3D depth impression of the observed scene. Example systems are described again focusing on their realization based on MPEG-4. Finally multi-view video coding is described as a key component for 3D and free viewpoint video systems. The conclusion is that the necessary technology including standard media formats for 3D and free viewpoint is available or will be available in the near future, and that there is a clear demand from industry and user side for such applications. 3D TV at home and free viewpoint video on DVD will be available soon, and will create huge new markets

We present a method for estimating 3D motion from 2D image sequences showing head and shoulder scenes typical of video telephone and teleconferencing applications. Our 3D model specifies the color and shape of the person in the video. Additionally, the model constrains facial motion and deformation to a set of facial expressions represented by the facial animation parameters (FAPs) defined by the MPEG-4 standard. Using this model, we obtain a description of both global and local 3D head motion as a function of the unknown facial parameters. Combining the 3D information with the optical flow constraint leads to a robust and linear algorithm that estimates the facial animation parameters from two successive frames with low computational complexity. Experimental results on synthetic and real data confirm the technique's applicability and show that image sequences of head and shoulder scenes can be encoded at bit rates below 0.6 Kbits.