ShareCam is a robotic pan, tilt, and zoom webbased camera controlled by simultaneous frame requests from online users. Part I describes the system. This paper, Part II, focuses on algorithms. The ShareCam problem is to find a camera frame that optimizes a measure of total user satisfaction. We present a grid-based approximation algorithm: given camera frame requests from n users, and approximation bound #, we analyze the tradeoff between solution quality and processing speed and prove that the algorithm runs in O(n/# ) time. The algorithm can be distributed to run in O(1/# ) time at each client and in O(n + 1/# ) time at the server. Experiments suggest that performance of the distributed algorithm degrades gracefully as clients fail to complete their part of the computation. ShareCam can be found online at: http://www.tele-actor.net/sharecam/.

ShareCam is a robotic pan, tilt, and zoom web-based camera controlled by simultaneous frame requests from online users. Part II describes algorithms. This paper, Part I, focuses on the system. Robotic webcameras are commercially available but currently restrict control to only one user at a time. ShareCam introduces a new interface that allows simultaneous control by many users. In this Java-based interface, participating users interact from their remotely located browsers where users draw desired frames over a fixed panoramic image. User inputs are transmitted back to a pair of PC servers that compute optimal camera parameters, servo the camera, and provide a video stream to all users. We describe the system, online experiments, and compare results with two frame selection models based on user ``satisfaction,'' one memoryless and the second based on satisfaction over multiple motion cycles. ShareCam is available online at: www.tele-actor.net/sharecam/

We consider a system that allows n networked users to share control over a robotic webcamera.

Abstract—New multi-axis satellites allow camera imaging parameters to be set during each time slot based on competing demand for images, specified as rectangular requested viewing zones over the camera’s reachable field of view. The single frame selection (SFS) problem is to find the camera frame parameters that maximize reward during each time window. We formalize the SFS problem based on a new reward metric that takes into account area coverage and image resolution. For a set of client requests and a satellite with discrete resolution levels, we give an algorithm that solves the SFS problem in time @ P A. For satellites with continuously variable resolution @ a A, we give an algorithm that runs in time @ QA. We have implemented all algorithms and verify performance using random inputs. Note to Practitioners—This paper is motivated by recent innovations in earth imaging by commercial satellites. In contrast to previous methods that required waits of up to 21 days for desired earth-satellite alignment, new satellites have onboard pan-tilt-zoom cameras that can be remotely directed to provide near real-time response to requests for images of specific areas on the earth’s surface. We consider the problem of resolving competing requests for images: Given client demand as a set of rectangles on the earth surface, compute camera settings that optimize the tradeoff between pan, tilt, and zoom parameters to maximize camera revenue during each time slot. We define a new quality metric and algorithms for solving the problem for the cases of discrete and continuous zoom values. These results are a step toward multiple frame selection which will be addressed in future research. The metric and algorithms presented in this paper may also be applied to collaborative teleoperation of ground-based robot cameras for inspection and videoconferencing and for scheduling astronomic telescopes. Index Terms—Camera, ground imaging, multi-axis, satellite, teleoperation, telerobotics.

Abstract—Deployed as a natural environment observatory or a surveillance device, a remote networked robotic pan-tilt-zoom camera needs to be controlled by simultaneous frame requests from both online users and in situ sensors such as motion detectors. This paper presents algorithms that are capable of finding a camera frame that optimizes a measure of total satisfaction over all requests, which is a generalized version of the single frame-selection problem proposed by Song et al. in 2006.We present a lattice-based approximation algorithm; given n requests and approximation bound ɛ, we analyze the tradeoff between solution quality and the corresponding computation time, and prove that the algorithm runs in O(n/ɛ3) time. We also develop a branch-and-bound-like implementation that reduces the constant factor of the algorithm by more than 70%. We have implemented the algorithms, and numerical experiment results conform to our analysis. Field experiments of the proposed algorithms have been conducted in the past three years. The proposed algorithms have been deployed successfully in a variety of real world applications including natural environment observation, building construction monitoring, and the surveillance of public space. Index Terms—Natural environment observation, pan-tilt-zoom camera, teleoperation, telerobotics. Z NOMENCLATURE =[z, z] is a set of feasible values of image resolution/camera zoom range. (x, y) Center position of a camera frame. z Camera frame size, z ∈ Z. c Camera frame c =[x, y, z]. c ∗ Optimal camera frame c ∗ =[x ∗,y ∗,z ∗]. n Number of request frames. zi Image resolution of the ith request, zi ∈ Z, i = 1,...,n. ri Request i, ri =[Ti,zi], where Ti is an arbitrary closed region, and it takes constant time to compute its area, i =1,...,n. Satisfaction function of request i. si

As a new application area for Automation, Near Real Time Satellite Imaging provides timely optical information which is used for weather prediction, disaster control, surveillance, and military applications. As the satellite passes over the earth, camera imaging parameters are changed to focus and capture data within requested zones. The Satellite Frame Selection problem arises when there are competing client requests: we want to automatically choose the satellite frame parameters that will maximize "reward" during each time window. In this paper we propose a new reward metric that incorporates both image resolution and coverage. For a set of n client requests we give a series of algorithms, the fastest computes optimal results in O(n ) for satellites with continuously variable resolution. We implement the algorithms and compare computation speed for all algorithms.

ShareCam is a robotic pan, tilt, and zoom streaming video camera controlled by simultaneous frame requests from remote users. Robotic webcameras are commercially available but currently restrict control to only one user at a time. ShareCam introduces a new interface that allows simultaneous control by many users. We will demonstrate the implemented system using a Java-based interface at the conference linked via the Internet to a camera on the UC Berkeley campus. We will also discuss system architecture and several new algorithms we've developed to compute optimal camera paramters based on user frame requests. ShareCam can be tested online at: www.tele-actor.net/sharecam/ Categories and Subject Descriptors H.4.3 [Information System Applications]: Communication Applications 1.

Systems and Algorithms for Collaborative Teleoperation Collaborative Teleoperation (CT) systems allow many users to simultaneously share control of a single remote physical resource such as a robot or human "explorer", with applications in education, health care, journalism, and entertainment. A primary challenge is scalable methods for computing consensus commands. This thesis combines results from two networked CT systems: one with a robotic webcamera (the Co-Opticon) and one with a human explorer (the Tele-Actor).

Collaborative Frame Selection arises when one robotic pan, tilt, zoom camera is shared by many users. The problem is to compute optimal camera parameters based on simultaneous frame requests from all users. We formalize the problem using a new metric, Intersection Over Maximum (IOM), to model the degree of satisfaction for each user, and seek to maximize total satisfaction for n users. We assume the zoom parameter is chosen from a discrete set of m levels and consider cases with discrete and continuous pan and tilt paramters. For a discrete set of w h pan and tilt values, we give an exact algorithm that runs in O((n + mwh) log n). For continuous pan and tilt, we give an exact algorithm that runs in O(n m) time. We also give a distributed version that runs in O(nm) time at each client and in O(n log n+mn) time at the server. An implementation of the second algorithm can be found online at: http://www.tele-actor.net/sharecam/.

INTRODUCTION Robotic streaming video cameras with pan, tilt, and zoom controls are now commercially available and are being installed in hundreds of locations around the world . Remote viewers can adjust camera parameters via the Internet to observe desired details in the scene. Current methods restrict control to one user at a time; users have to wait in a queue for their turn to operate the camera. In this thesis, we develop ShareCam, a new approach that eliminates the queue and allows many users to access and share control of the robotic camera simultaneously. Since conflicting frame requests are made by users, a primary challenge is computing optimal camera parameters. We formalize the problem using a new metric, Intersection Over Maximum (IOM), to model the degree of satisfaction for each user, and seek to maximize total satisfaction for n users. We develop online algorithms to solve this optimization problem for cases where pan, tilt and zoom values can be either discrete or