Mobile ad hoc networks (MANETs) that consist of smartphones can be configured easily because most of them are equipped with cellular (3G/LTE) connections as well as WiFi/Bluetooth connections, and then new network systems and services over MANETs can be developed and implemented. However, the performance of the new network systems and services should be evaluated in MANET field experiments. In this paper, we develop a real-time system on Android terminals for visualizing network topology and packet flow in the network to conduct efficient MANET field experiments. Whenever Android terminals communicate with the neigh boring terminals over MANETs, each Android terminal can grasp the information on the neigh boring terminals, and then it sends the information on the neigh boring terminals and the packet reception logs to the log management server. Each terminal can visualize the network topology and packet flow based on these information obtained from the server in real time through cellular connections. As a result, thanks to the visualizing system, the network topology and the packet flow in the network can be confirmed in real time, and then the MANET field experiments can be conducted more efficiently. Finally, we can analyze the log data in the server to evaluate the MANET-based application software after we conducted the MANET field experiments.

We focus on a challenging trial of a Look-Change mixed reality (MR) space. Look refers to perceived ambience of an image created by illumination and color tone. Regarding the Look-Change, we have been working on a relighting technique which allows MR space to have additional virtual illumination. Furthermore, we demonstrate a photorealistic approach to create photorealistic virtual objects with free-form polarized reflectometry which requires no specialized hardware and is portable, thus making it easy apply to MR.

We present a prototype system for in-situ measurement of per-pixel appearance parameters (i.e., surface orientation, diffuse albedo, specular albedo, and specular roughness) of general scenes. The proposed system requires no specialized hardware, is light weight, and requires no on-site calibration. This makes our system particularly well suited for capturing the appearance of real-world scenes under uncontrolled conditions.