An autonomous robot photographer

Byers, Zachary; Dixon, Michael; Goodier, K.; Grimm, Cindy; Smart, William D.

doi:10.1109/iros.2003.1249268

Cited by 50 publications

(39 citation statements)

References 15 publications

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“…While much work has been done on 3D camera control in scenes (e.g., Drucker and Zeltzer [1995] and Byers et al [2003]), full 3D camera control is outside of our scope, and we refer to the excellent taxonomy of general methods for camera control in 3D by Christie et al [2008]. Several researchers have investigated ways of evaluating the goodness of a view.…”

Section: Related Workmentioning

confidence: 99%

Perceptual models of viewpoint preference

et al. 2011

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The question of what are good views of a 3D object has been addressed by numerous researchers in perception, computer vision, and computer graphics. This has led to a large variety of measures for the goodness of views as well as some special-case viewpoint selection algorithms. In this article, we leverage the results of a large user study to optimize the parameters of a general model for viewpoint goodness, such that the fitted model can predict people's preferred views for a broad range of objects. Our model is represented as a combination of attributes known to be important for view selection, such as projected model area and silhouette length. Moreover, this framework can easily incorporate new attributes in the future, based on the data from our existing study. We demonstrate our combined goodness measure in a number of applications, such as automatically selecting a good set of representative views, optimizing camera orbits to pass through good views and avoid bad views, and trackball controls that gently guide the viewer towards better views.

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Section: Related Workmentioning

confidence: 99%

Perceptual models of viewpoint preference

et al. 2011

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“…Approaches to people tracking in robotics can be classified according to the used sensor, e.g., laser scanners [1], [7], monocular cameras [3], stereo cameras [6], IMUs [16], or combinations of these sensors [4], [10], [12], [19], [21].…”

Section: Related Workmentioning

confidence: 99%

Accurate human motion capture in large areas by combining IMU- and laser-based people tracking

Ziegler

Kretzschmar

Stachniss

et al. 2011

2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-A large number of applications use motion capture systems to track the location and the body posture of people. For instance, the movie industry captures actors to animate virtual characters that perform stunts. Today's tracking systems either operate with statically mounted cameras and thus can be used in confined areas only or rely on inertial sensors that allow for free and large-scale motion but suffer from drift in the pose estimate. This paper presents a novel tracking approach that aims to provide globally aligned full body posture estimates by combining a mobile robot and an inertial motion capture system. In our approach, a mobile robot equipped with a laser scanner is used to anchor the pose estimates of a person given a map of the environment. It uses a particle filter to globally localize a person wearing a motion capture suit and to robustly track the person's position. To obtain a smooth and globally aligned trajectory of the person, we solve a least squares optimization problem formulated from the motion capture suite and tracking data. Our approach has been implemented on a real robot and exhaustively tested. As the experimental evaluation shows, our system is able to provide locally precise and globally aligned estimates of the person's full body posture.

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“…They were realized to digitalize the subjective evaluation of humans in the research. Furthermore, Byers et al [10], [11] tried to combine composition evaluation with viewpoint selection. In case of events or a ceremony where people are moving and talking to each other, they proposed a complete, end-to-end system for capturing an aesthetic photograph based on the Rule of thirds.…”

Section: Introductionmentioning

confidence: 99%

Autonomous Viewpoint Selection of Robot Based on Aesthetic Evaluation of a Scene

Lan

Sekiyama

2016

Journal of Artificial Intelligence and Soft Computing Research

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In this paper, we propose an optimal viewpoint selection system for monitoring robots to search for the optimal viewpoint of a scene with the highest aesthetic property. Using the information of the targets, we propose a novel method for predicting human aesthetic sense for a scene. We construct evaluation functions based on certain known composition rules using three factors, namely, target size, visual balance, and composition fitting value. Then a score, which is a reflection of human evaluation, will be obtained using these functions. The optimal viewpoint will be selected from a number of candidates around the target group, by evaluating the aesthetic properties of scenes for each candidate viewpoint. Finally, once the optimal viewpoint is confirmed, path planning and path following controls are implemented for the robots during the moving process.

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An autonomous robot photographer

Cited by 50 publications

References 15 publications

Perceptual models of viewpoint preference

Perceptual models of viewpoint preference

Accurate human motion capture in large areas by combining IMU- and laser-based people tracking

Autonomous Viewpoint Selection of Robot Based on Aesthetic Evaluation of a Scene

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