TRISK: A local features extraction framework for texture-plus-depth content matching
نویسندگان
چکیده
منابع مشابه
Local visual features extraction from texture+depth content based on depth image analysis
With the increasing availability of low-cost – yet precise – depth cameras, “texture+depth” content has become more and more popular in several computer vision and 3D rendering tasks. Indeed, depth images bring enriched geometrical information about the scene which would be hard and often impossible to estimate from conventional texture pictures. In this paper, we investigate how the geometric ...
متن کاملA Novel Method for Content Base Image Retrieval Using Combination of Local and Global Features
Content-based image retrieval (CBIR) has been an active research topic in the last decade. In this paper we proposed an image retrieval method using global and local features. Firstly, for local features extraction, SURF algorithm produces a set of interest points for each image and a set of 64-dimensional descriptors for each interest points and then to use Bag of Visual Words model, a cluster...
متن کاملA Novel Method for Content Base Image Retrieval Using Combination of Local and Global Features
Content-based image retrieval (CBIR) has been an active research topic in the last decade. In this paper we proposed an image retrieval method using global and local features. Firstly, for local features extraction, SURF algorithm produces a set of interest points for each image and a set of 64-dimensional descriptors for each interest points and then to use Bag of Visual Words model, a cluster...
متن کاملTexture Features for Content-Based Retrieval
Texture is an intuitive concept Every child knows that leopards have spots but tigers have stripes that curly hair looks di erent from straight hair etc In all these examples there are variations of intensity and color which form certain repeated patterns called visual texture The patterns can be the result of physical surface properties such as roughness or oriented strands which often have a ...
متن کاملLocal Features and Kernels for Classification of Texture and Object Categories: An In-Depth Study
Recently, methods based on local image features have shown promise for texture and object recognition tasks. This paper presents a large-scale evaluation of an approach that represents images as distributions (signatures or histograms) of features extracted from a sparse set of keypoint locations and learns a Support Vector Machine classifier with kernels based on two effective measures for com...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Image and Vision Computing
سال: 2018
ISSN: 0262-8856
DOI: 10.1016/j.imavis.2017.11.007