Hiromi Hirano

Protecting against screenshots: An image processing approach

Motivated by reasons related to data security and privacy, we propose a method to limit meaningful visual contents of a display from being captured by screenshots. Traditional methods take a system architectural approach to protect against screenshots. We depart from this framework, and instead exploit image processing techniques to distort visual data of a display and present the distorted data to the viewer. Given that a screenshot captures distorted visual contents, it yields limited useful data. We exploit the human visual system to empower viewers to automatically and mentally recover the distorted contents into a meaningful form in real-time. Towards this end, we leverage on findings from psychological studies which show that blending of visual information from recent and current fixations enables human to form meaningful representation of a scene. We model this blending of information by an additive process, and exploit this to design a visual contents distortion algorithm that supports real-time contents recovery by the human visual system. Our experiments and user study demonstrate the feasibility of our method to allow viewers to readily interpret visual contents of a display, while limiting meaningful contents from being captured by screenshots.

Cyber Chamber: Multi-user Collaborative Assistance System for Online Shopping

Recently, online shopping continues to thrive in modern societies, especially via tablets and smartphones; however, in current online shopping environments, there is insufficient support for shopping with several people, which is often what shoppers do together in the nonvirtual world. In this paper, we propose a novel system that provides a new online shopping experience for multiple users. Here, we developed Cyber Chamber, a system that enables users to interact with tablets and wall projection for each user to search items privately via their tablets and then share those publicly on the wall. To evaluate the effectiveness of our system, we performed experiments. From our results, we confirmed that our proposed system successfully supports the ease of discussion, information sharing, and ease with which multiple users can together consider combinations of goods.

Video retrieval based on user-specified deformation

Lets assume that we are now watching the scene of Fig. 1-a, where a red racing car is running from left to right. At the same time, we feel like watching another scene like Fig. 1-b, where a similar car is running toward us. To find such a desired scene, we usually push the forward and rewind buttons or move the play bar. If we cannot find the scene in the currently watching video, we have to go to a video sharing service like YouTube to further search for it. However, these are tedious tasks. Goldman et al. propose a method to navigate a single video [2008], but we want to find a scene not only in a single video but also a different video from the currently watching one.