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Showing papers by "Matthew Turk published in 2010"


Proceedings ArticleDOI
TL;DR: This work review and categorize algorithms for contentaware image retargeting, i.e., resizing an image while taking its content into consideration to preserve important regions and minimize distortions, as it requires preserving the relevant information while maintaining an aesthetically pleasing image for the user.
Abstract: Advances in imaging technology have made the capture and display of digital images ubiquitous. A variety of displays are used to view them, ranging from high-resolution computer monitors to low-resolution mobile devices, and images often have to undergo changes in size and aspect ratio to adapt to different screens. Also, displaying and printing documents with embedded images frequently entail resizing of the images to comply with the overall layout. Straightforward image resizing operators, such as scaling, often do not produce satisfactory results, since they are oblivious to image content. In this work, we review and categorize algorithms for contentaware image retargeting, i.e., resizing an image while taking its content into consideration to preserve important regions and minimize distortions. This is a challenging problem, as it requires preserving the relevant information while maintaining an aesthetically pleasing image for the user. The techniques typically start by computing an importance map which represents the relevance of every pixel, and then apply an operator that resizes the image while taking into account the importance map and additional constraints. We intend this review to be useful to researchers and practitioners interested in image retargeting.

146 citations


Proceedings ArticleDOI
13 Jun 2010
TL;DR: An approach to indoor localization and pose estimation in order to support augmented reality applications on a mobile phone platform and evaluates the algorithm performance as well as its accuracy in terms of reprojection distance of the 3D virtual objects in the cell phone image.
Abstract: The computational capability of mobile phones has been rapidly increasing, to the point where augmented reality has become feasible on cell phones. We present an approach to indoor localization and pose estimation in order to support augmented reality applications on a mobile phone platform. Using the embedded camera, the application localizes the device in a familiar environment and determines its orientation. Once the 6 DOF pose is determined, 3D virtual objects from a database can be projected into the image and displayed for the mobile user. Off-line data acquisition consists of acquiring images at different locations in the environment. The online pose estimation is done by a feature-based matching between the cell phone image and an image selected from the precomputed database using the phone's sensors (accelerometer and magnetometer). The application enables the user both to visualize virtual objects in the camera image and to localize the user in a familiar environment. We describe in detail the process of building the database and the pose estimation algorithm used on the mobile phone. We evaluate the algorithm performance as well as its accuracy in terms of reprojection distance of the 3D virtual objects in the cell phone image.

83 citations


Proceedings ArticleDOI
23 Aug 2010
TL;DR: A method for human activity recognition in videos, based on shape analysis, that achieves an accuracy of 87%, and is comparable to other state-of-the-art methods.
Abstract: We propose a method for human activity recognition in videos, based on shape analysis. We define local shape descriptors for interest points on the detected contour of the human action and build an action descriptor using a Bag of Features method. We also use the temporal relation among matching interest points across successive video frames. Further, an SVM is trained on these action descriptors to classify the activity in the scene. The method is invariant to the length of the video sequence, and hence it is suitable in online activity recognition. We have demonstrated the results on an action database consisting of nine actions like walk, jump, bend, etc., by twenty people, in indoor and outdoor scenarios. The proposed method achieves an accuracy of 87%, and is comparable to other state-of-the-art methods.

8 citations


Journal ArticleDOI
TL;DR: In this paper, a parameterized structured light imaging that is practically useful for detecting depth edges is presented. But the method is limited to the detection of silhouette edges for visual hull reconstruction.
Abstract: This reported research features parameterised structured light imaging that is practically useful for detecting depth edges. Given input parameters such as the range of distances of an object from the camera/projector and minimum detectable depth difference, the presented method is capable of computing an optimal pattern width and the number of structured light images that are needed to detect all depth edges in the specified range of distances that have at least the given detectable depth difference. Application of this parameter control to the detection of silhouette edges for visual hull reconstruction shows the effectiveness of the method.

4 citations


Journal Article
TL;DR: In this paper, a parameterized structured light imaging that is practically useful for detecting depth edges is presented. But the method is limited to the detection of silhouette edges for visual hull reconstruction.
Abstract: This reported research features parameterised structured light imaging that is practically useful for detecting depth edges. Given input parameters such as the range of distances of an object from the camera/projector and minimum detectable depth difference, the presented method is capable of computing an optimal pattern width and the number of structured light images that are needed to detect all depth edges in the specified range of distances that have at least the given detectable depth difference. Application of this parameter control to the detection of silhouette edges for visual hull reconstruction shows the effectiveness of the method.