Appearance indexing
نویسنده
چکیده
Although it is very hard to quantify the visual impression of an image, we conjecture that the overall visual appearance of an image may be the combined effect of the appearances of image patches of various shapes and sizes. We can imagine that all possible appearances of image patches of all possible shapes and sizes form a conceptual appearance space. Each point in the appearance space therefore corresponds to a certain combination of the object parameters (shape, size, surface texture, pose, orientation, etc) and the imaging conditions (illuminating source, viewing angle, sensor response etc.). Using real sensor data and unsupervised learning, statistically most representative appearance prototypes can be found to approximate the appearance space. Statistics of these appearance prototypes present in an image therefore characterize the image content, which in turn can be used to perform tasks such as content-based image retrieval.
منابع مشابه
Image indexing using a colored pattern appearance model
We introduce a new method for colour image indexing and content-based image retrieval. An image is divided into small sub-images and the visual appearance of which is characterised by a coloured pattern appearance model. The statistics of the local visual appearance of the image are then computed as measures of the global visual appearance of the image. The visual appearance of the small sub-im...
متن کاملAppearance Based Indexing for Relocalisation in Real-Time Visual SLAM
Previous work on visual SLAM has shown that indexing on space and scale facilitates the use of feature descriptors for matching in real-time systems and that this can significantly increase robustness. However, the performance gains necessarily diminish as uncertainty about camera position increases. In this paper we address this issue by introducing a further level of indexing based on appeara...
متن کاملTowards large-scale geometry indexing by feature selection
We present a new approach to image indexing and retrieval, which integrates appearance with global image geometry in the indexing process, while enjoying robustness against viewpoint change, photometric variations, occlusion, and background clutter. We exploit shape parameters of local features to estimate image alignment via a single correspondence. Then, for each feature, we construct a spars...
متن کاملImage Indexing and Retrieval Using Image-Derived, Geometrically and Illumination Invariant Features
In this paper, we propose novel image-derived features for image indexing and retrieval in digital library applications. The new features capture the intrinsic geometry and color properties of an imaged object. That is, these features are insensitive to the change of an object's appearance due to incidental environmental factors such as rigid motion, a ne shape deformation, changes of parameter...
متن کاملEfficient Matching and Indexing of Graph Models in Content-Based Retrieval
ÐIn retrieval from image databases, evaluation of similarity, based both on the appearance of spatial entities and on their mutual relationships, depends on content representation based on Attributed Relational Graphs. This kind of modeling entails complex matching and indexing, which presently prevents its usage within comprehensive applications. In this paper, we provide a graphtheoretical fo...
متن کاملتأملاتی بر نمایه سازی تصاویر: یک تصویر ارزشی برابر با هزار واژه
Purpose: This paper presents various image indexing techniques and discusses their advantages and limitations. Methodology: conducting a review of the literature review, it identifies three main image indexing techniques, namely concept-based image indexing, content-based image indexing and folksonomy. It then describes each technique. Findings: Concept-based image indexing is te...
متن کامل