Increasing Realism and Supporting Content Planning for Dynamic Scenes in a Mixed Reality System incorporating a Time-of-Flight Camera

For broadcasting purposes MIXED REALITY, the combination of real and virtual scene content, has become ubiquitous nowadays. Mixed Reality recording still requires expensive studio setups and is often limited to simple color keying. We present a system for Mixed Reality applications which uses depth keying and provides threedimensional mixing of real and artificial content. It features enhanced realism through automatic shadow computation which we consider a core issue to obtain realism and a convincing visual perception, besides the correct alignment of the two modalities and correct occlusion handling. Furthermore we present a possibility to support placement of virtual content in the scene. Core feature of our system is the incorporation of a TIME-OF-FLIGHT (TOF)-camera device. This device delivers real-time depth images of the environment at a reasonable resolution and quality. This camera is used to build a static environment model and it also allows correct handling of mutual occlusions between real and virtual content, shadow computation and enhanced content planning. The presented system is inexpensive, compact, mobile, flexible and provides convenient calibration procedures. Chroma-keying is replaced by depth-keying which is efficiently performed on the GRAPHICS PROCESSING UNIT (GPU) by the usage of an environment model and the current ToF-camera image. Automatic extraction and tracking of dynamic scene content is herewith performed and this information is used for planning and alignment of virtual content. An additional sustainable feature is that depth maps of the mixed content are available in real-time, which makes the approach suitable for future 3DTV productions. The presented paper gives an overview of the whole system approach including camera calibration, environment model generation, real-time keying and mixing of virtual and real content, shadowing for virtual content and dynamic object tracking for content planning.

Early Versus Late Effort in Dynamic Agencies with Unverifiable Information

In this paper we analyze a dynamic agency problem where contracting parties do not know the agent's future productivity at the beginning of the relationship. We consider a two-period model where both the agent and the principal observe the agent's second-period productivity at the end of the first period. This observation is assumed to be non-verifiable information. We compare long-term contracts with short-term contracts with respect to their suitability to motivate effort in both periods. On the one hand, short-term contracts allow for a better fine-tuning of second-period incentives as they can be aligned with the agent's second-period productivity. On the other hand, in short-term contracts first-period effort incentives might be distorted as contracts have to be sequentially optimal. Hence, the difference between long-term and short-term contracts is characterized by a trade-off between inducing effort in the first and in the second period. We analyze the determinants of this trade-off and demonstrate its implications for performance measurement and information system design.

GPU-based Ray Tracing of Dynamic Scenes

Interactive ray tracing of non-trivial scenes is just becoming feasible on single graphics processing units (GPU). Recent work in this area focuses on building effective acceleration structures, which work well under the constraints of current GPUs. Most approaches are targeted at static scenes and only allow navigation in the virtual scene. So far support for dynamic scenes has not been considered for GPU implementations. We have developed a GPU-based ray tracing system for dynamic scenes consisting of a set of individual objects. Each object may independently move around, but its geometry and topology are static.

Dynamic merge of discrete goods flow – Impact on throughput and efficiency

Continuous conveyors with a dynamic merge were developed with adaptable control equipment to differentiate these merges from competing Stop-and-Go merges. With a dynamic merge, the partial flows are manipulated by influencing speeds so that transport units need not stop for the merge. This leads to a more uniform flow of materials, which is qualitatively observable and verifiable in long-term measurements. And although this type of merge is visually mesmerizing, does it lead to advantages from the view of material flow technology? Our study with real data indicates that a dynamic merge shows a 24% increase in performance, but only for symmetric or nearly symmetric flows. This performance advantage decreases as the flows become less symmetric, approaching the throughput of traditional Stop-and-Go merges. And with a cost premium for a continuous merge of approximately 10% due to the additional technical components (belt conveyor, adjustable drive engines, software, etc.), this restricts their economical use.