We evaluate the performance of MPEG-7 image signatures, Compressed Histogram of Gradients descriptor (CHoG) and Scale Invariant Feature Transform (SIFT) descriptors for mobile vis...
Vijay Chandrasekhar, David M. Chen, Andy Lin, Gabr...
Abstract--This paper proposes a parallel hardware architecture for image feature detection based on the SIFT (Scale Invariant Feature Transform) algorithm and applied to the SLAM (...
Vanderlei Bonato, Eduardo Marques, George A. Const...
The Scale Invariant Feature Transform, SIFT, has been successfully applied to robot localization. Still, the number of features extracted with this approach is immense, especially...
Most of the existing image retrieval systems take the textual query from the user and utilize the metadata associated with the database images to retrieve the result. However, the...
In this paper, we address the problem of identifying and localizing multiple instances of highly deformable objects in real-time video data. We present an approach which uses PCA-...
Abstract. The Scale Invariant Feature Transform (SIFT) has become a popular feature extractor for vision-based applications. It has been successfully applied to metric localization...
Recent years have seen an increased interest in motion capture systems. Current systems, however, are limited to only a few degrees of freedom, so that effectively only the motion...
This paper addresses the problem of content-based synchronization for robust watermarking. Synchronization is a process of extracting the location to embed and detect the signature...
Hae-Yeoun Lee, Jong-Tae Kim, Heung-Kyu Lee, Young-...
Current feature-based object recognition methods use information derived from local image patches. For robustness, features are engineered for invariance to various transformation...
— This paper presents an approach to vision-based simultaneous localization and mapping (SLAM). Our approach uses the scale invariant feature transform (SIFT) as features and app...