Performance Evaluation of SIFT - Based Descriptors for Object Recognition
نویسنده
چکیده
Object recognition has become one of the most active research topics in computer vision in recent years. The set of features extracted from the training image is critical for good object recognition performance. The Scale Invariant Feature Transform (SIFT) was proposed by David Lowe in 1999; the SIFT features are local and effective for object recognition. In this paper we conducted a survey of recent related work on the SIFT descriptor, analyzed the evaluation criteria for object recognition, and analyzed the performance of the SIFT descriptor and extended SIFT descriptors based on common properties and evaluation criterion. The paper documents improvement strategies and trends of the SIFT descriptor and proposed extensions.
منابع مشابه
Performance evaluation of block-based copy- move image forgery detection algorithms
Copy-move forgery is a particular type of distortion where a part or portions of one image is/are copied to other parts of the same image. This type of manipulation is done to hide a particular part of the image or to copy one or more objects into the same image. There are several methods for detecting copy-move forgery, including block-based and key point-based methods. In this paper, a method...
متن کاملNew Robust Descriptor for Image Matching
Nowadays, object recognition based on feature extraction is widely used in image matching due to its robustness to different types of image transformations. This paper introduces a new approach for extracting invariant features from interest regions. This approach is inspired from the well known Scale Invariant Feature Transform (SIFT) interest points detector and aims to improve the computatio...
متن کاملColor orthogonal local binary patterns combination for image region description
Visual content description is a key issue for machine-based image analysis and understanding. A good visual descriptor should be both discriminative enough and computationally efficient while possessing some properties of robustness to viewpoint changes and lighting condition variations. In this paper, we propose several new local descriptors based on color orthogonal local binary patterns comb...
متن کاملPerformance Evaluation of Local Descriptors for Affine Invariant Region Detector
Local feature descriptors are widely used in many computer vision applications. Over the past couple of decades, several local feature descriptors have been proposed which are robust to challenging conditions. Since they show different characteristics in different environment, it is necessary to evaluate their performance in an intensive and consistent manner. However, there has been no relevan...
متن کاملBinary Co-occurrences of Weak Descriptors
This paper demonstrates that a reliable and efficient object recognition system based only on binary joint occurrences of quantized descriptors can be built. Specifically, we show that a high recognition performance can be obtained even with very weak (non discriminative) descriptors. The binary joint occurrence representation despite being high dimensional is very sparse and therefore efficien...
متن کامل