Implementing “Visual Categorization with Bag of Keypoints”

نویسنده

  • Jason Yosinski
چکیده

First of all, we downloaded 8 directories from Caltech 101, and used “sift.m” as a function by David Lowe to get SIFT descriptors from each image. However, it took almost forever when we used 8 directories. Therefore, we ended up using only 3 directories: anchors, elephants, and helicopters. By using function ‘sift’ we gathered many descriptors for each image. Some of the images and their SIFT features are shown in Figure 1.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Visual Categorization with Bags of Keypoints

We present a novel method for generic visual categorization: the problem of identifying the object content of natural images while generalizing across variations inherent to the object class. This bag of keypoints method is based on vector quantization of affine invariant descriptors of image patches. We propose and compare two alternative implementations using different classifiers: Naïve Baye...

متن کامل

Improving “bag-of-keypoints” image categorisation: Generative Models and PDF-Kernels

In this paper we propose two distinct enhancements to the basic “bag-of-keypoints” image categorisation scheme proposed in [4]. In this approach images are represented as a variable sized set of local image features (keypoints). Thus, we require machine learning tools which can operate on sets of vectors. In [4] this is achieved by representing the set as a histogram over bins found by k-means....

متن کامل

"Bag of keypoints"-based biomedical image search with affine covariant region detection and correlation-enhanced similarity matching

This paper presents a “bag of keypoints” based biomedical image retrieval approach by detecting affine covariant regions. The covariant regions simply refers to a set of pixels or interest points which are invariant to affine transformations, as well as occlusion, lighting and intra-class variations. To describe the intensity pattern within the interest points the Scale-Invariant Feature Transf...

متن کامل

Image Categorization and Semantic Segmentation using Scale-Optimized Textons

In computer vision research, a texton is a representative dense visual word for the bag-of-keypoints method. It has proven its effectiveness in categorizing materials and in generic object classes. Despite its success and popularity, no report describes a study that has tackled the problem of its scale optimization for given image data and associated object categories. We propose scale-optimize...

متن کامل

Multi-scale Cortical Keypoint Representation for Attention and Object Detection

Keypoints (junctions) provide important information for focus-of-attention (FoA) and object categorization/recognition. In this paper we analyze the multi-scale keypoint representation, obtained by applying a linear and quasi-continuous scaling to an optimized model of cortical end-stopped cells, in order to study its importance and possibilities for developing a visual, cortical architecture. ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2006