Many cloud platforms emerge to meet urgent requirements for large-volume personal image store, sharing and search. Though most would agree that images contain rich sensitive information (e.g., People, location and event) and people's privacy concerns hinder their participation into untrusted services, today's cloud platforms provide little support for image privacy protection. Facing large-scale images from multiple users, it is extremely challenging for the cloud to maintain the index structure and schedule parallel computation without learning anything about the image content and indices. In this work, we introduce a novel system PIC: a Privacy-preserving Image search system on Cloud, which is a step towards feasible cloud services which provide secure content-based large-scale image search with fine-grained access control. Users can search on others' images if they are authorized by the image owners. Majority of the computationally intensive jobs are handled by the cloud, and a querier can now simply send the query and receive the result. Specially, to deal with massive images, we design our system suitable for distributed and parallel computation and introduce several optimizations to further expedite the search process. Our security analysis and prototype system evaluation results show that PIC successfully protects the image privacy at a low cost of computation and communication.

With the rapid development of mobile applications, there is an urgent need for highly efficient indoor localization service. Dedicated systems achieve good accuracy at the cost of deploying special hardware. Fingerprint-based methods avoid maintaining the expensive infrastructure but suffer from intensive labor for site-survey and poor robustness. In this paper, we present Per Loc, an infrastructure-free localization system which leverages rich vision features in indoor environment with high efficiency and accuracy. Per Loc makes use of binocular ranging technique to calculate the depth of a feature point and then figures out its geographical coordinates to build up reference point database, for which we design a filtering scheme to keep the database efficient in storage and search delay. During the localization stage, users simply take a photo of surroundings and feature points are extracted automatically as input for search scheme. Then a fast two-stage search scheme is proposed to find the nearest neighbors of query feature points in reference point database. Based on the perspective projection model, we inversely calculate users' geographical location in real time. We implement the proposed localization system on commercial smartphones as well as laptops and conduct extensive experiments. Per Loc achieves 1.76m of average error in office environment, and 2.2m of average error in shopping mall.

In this work, we explore a new networking mechanism with smart glasses, through which users can express their interest and connect to a target simply by a gaze. Doing this, we attempt to let wearable devices understand human attention and intention, and pair devices carried by users according to such attention and intention. To achieve this ambitious goal, we propose a proof-of-concept system iGaze, a visual attention driven networking suite: an iGaze glass (hardware), and a networking protocol VAN (software). Our glass, iGaze glass, is a low-cost head-mounted glass with a camera, orientation sensors, microphone and speakers, which are embedded with our software for visual attention capture and networking. A visual attention driven networking protocol (VAN) is carefully designed and implemented. In VAN, we design an energy efficient and highly accurate visual attention determination scheme using single camera to capture user's communication interest and a double-matching scheme based on visual direction detection and Doppler effect of acoustic signal to lock the target devices. Using our system, we conduct a series of trials for various application scenarios to demonstrate the effectiveness of our system.

In this demo, we propose a proof-of-concept networking system for smart glasses, through which users can express their interest and connect to a target simply by a gaze. Our system iGaze is a visual attention driven networking suite: an iGaze glass (hardware) and a networking protocol VAN (software). Our glass is a low-cost head-mounted glass with a camera, orientation sensors, microphone and speakers, which are embedded with our software for visual attention capture and networking. A visual attention driven networking protocol (VAN) is carefully designed and implemented. In VAN, we design an energy efficient and highly accurate visual attention determination scheme using single camera to capture user's communication interest and a double-matching scheme based on visual direction detection and Doppler effect of acoustic signal to lock the target devices. iGaze has separated and modularized hardware and software design. It can run on top of existing networking protocols, e.g., Wi-Fi.