Computer graphics: principles and practice (2nd ed.)
Computer graphics: principles and practice (2nd ed.)
Tile size selection using cache organization and data layout
PLDI '95 Proceedings of the ACM SIGPLAN 1995 conference on Programming language design and implementation
Computer Vision and Image Understanding
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design
Efficient Extraction of Robust Image Features on Mobile Devices
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
Pose tracking from natural features on mobile phones
ISMAR '08 Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality
Faster and Better: A Machine Learning Approach to Corner Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
BRIEF: binary robust independent elementary features
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Large-scale EMM identification based on geometry-constrained visual word correspondence voting
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Evaluation of Interest Point Detectors and Feature Descriptors for Visual Tracking
International Journal of Computer Vision
EFFEX: an embedded processor for computer vision based feature extraction
Proceedings of the 48th Design Automation Conference
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Machine learning for high-speed corner detection
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Real-time panoramic mapping and tracking on mobile phones
VR '10 Proceedings of the 2010 IEEE Virtual Reality Conference
ORB: An efficient alternative to SIFT or SURF
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
MEVBench: A mobile computer vision benchmarking suite
IISWC '11 Proceedings of the 2011 IEEE International Symposium on Workload Characterization
Listen, look, and gotcha: instant video search with mobile phones by layered audio-video indexing
Proceedings of the 21st ACM international conference on Multimedia
Enabling low bitrate mobile visual recognition: a performance versus bandwidth evaluation
Proceedings of the 21st ACM international conference on Multimedia
EVA: an efficient vision architecture for mobile systems
Proceedings of the 2013 International Conference on Compilers, Architectures and Synthesis for Embedded Systems
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Running a SURF (Speeded Up Robust Features) detector on mobile devices remains too slow to support emerging applications such as mobile augmented reality. Porting it without adapting the algorithm to account for mobile platform limitations could result in significant runtime degradation. In this paper, we identify two mismatches between the SURF algorithm and the mobile hardware that cause substantial slow-down of the point detection process: 1) mismatch between the data access pattern and the small cache size, and 2) mismatch between the huge amount of branches and high pipeline hazard penalty. To address the mismatches, we propose two techniques: tiled SURF and gradient moment based orientation assignment. Tiled SURF improves data locality and greatly reduces memory traffic. A method for determining the optimal tile sizes, named content-aware tiling, is designed to minimize runtime and maximize detection accuracy. To avoid the penalties caused by pipeline hazards, we replace the original orientation operator with branching-free gradient moment computations. The proposed techniques are tested on three mobile platforms. Comparing to the original SURF, the accelerated SURF achieves a 6x~8x speedup without sacrificing recognition accuracy. Meanwhile, it achieves 59%~80% reductions in the runtime ratio of the detector running on mobile platforms compared with on x86-based PCs.