To aid visitors of art centers in automatically identifying an object of interest, a computer vision algorithm known as SIFT has been implemented using MATLAB. Salient aspects of the algorithm have been discussed in light of image recognition applications. Test methods to validate the algorithm have been detailed out. Performance improvement for SIFT also has been proposed.

Aiming at solving lengthy time-consuming registration and mismatch problems caused by images which have feature simliarity of local region in the traditional SIFT (Scale Invariant Feature Transform) registration method, a fine registration method based on geometric constraints and parallel architecture is put forward. First, in order to provide geometric constraints for block and fine registrat...

We propose a novel framework called StochasticSIFT for detecting interest points (IPs) in video sequences. The proposed framework incorporates a stochastic model considering the temporal dynamics of videos into the SIFT detector to improve robustness against fluctuations inherent to video signals. Instead of detecting IPs and then removing unstable or inconsistent IP candidates, we introduce IP...

In this work we deal with the problem of how different local descriptors can be extended, used and combined for improving the effectiveness of video concept detection. The main contributions of this work are: 1) We examine how effectively a binary local descriptor, namely ORB, which was originally proposed for similarity matching between local image patches, can be used in the task of video con...

In most conventional systems for new viewpoint video synthesis of a moving object, calibrated multiple fixed cameras are used. Field of view of every camera must cover all the area in which the object moves. If the area is large, object size in the captured images and also in the new viewpoint video will become very small. In this paper, we propose a novel method to synthesize new viewpoint vid...

Image matching is a research focus in the field of image processing. The method based on feature matching by researchers alike for Its stable performance. Based on the analysis of the traditional SIFT algorithm, For computationally intensive problems of SIFT feature descriptor links, Proposed a new descriptor generation algorithm. Experimental results show that this method can effectively reduc...

We present a method for detecting and describing features in vector flow fields. Our method models flow fields locally using a linear combination of complex monomials. These monomials form an orthogonal basis for analytic flows with respect to a correlation-based innerproduct. We investigate the invariance properties of the coefficients of the approximation polynomials under both rotation and s...

As with many large organizations, the Government's data is split in many different ways and is collected at different times by different people. The resulting massive data heterogeneity means that government staff cannot effectively locate, share, or compare data across sources, let alone achieve computational data interoperability. The premise of our research is that it is possible to signific...

The absorption of the light by sea water and light scattering by small particles of underwater environment has become an obstacle of underwater vision researches with camera. It gives impact to the limitation of visibility distances camera in the sea water. The research of 3D reconstruction requires image matching technique to find out the keypoints of image pairs. SIFT is one of the image matc...

This paper presents a methodology for tracking a hypoor hyper-enhanced focal liver lesion (FLL) and a healthy liver region in a video sequence of a Contrast-Enhanced Ultrasound (CEUS) examination. The outcome allows the differentiation between benign and malignant cases, by characterising FLLs of typical behaviour, according to their Time-Intensity curves. The task is challenging mainly due to ...