Viewpoint Invariant Scene Retrieval using Textured Regions
نویسنده
چکیده
We describe progress in matching shots which are images of the same 3D scene in a film. The problem is hard because the camera viewpoint may change substantially between shots, with consequent changes in the imaged appearance of the scene due to foreshortening, scale changes and partial occlusion. We demonstrate that wide baseline matching techniques can be successfully employed for this task by matching key frames between shots. The wide baseline method represents each frame by a set of viewpoint invariant local feature vectors. The local spatial support of the features means that segmentation of the frame (e.g. into foreground/background) is not required, and partial occlusion is tolerated. We contrast this local method with a texture region descriptor which is invariant to affine geometric and photometric transformations, and insensitive to the shape of the texture region. It is applicable to texture patches which are locally planar and have stationary statistics. The novelty of the descriptor is that it is based on statistics aggregated over the region, resulting in richer and more stable descriptors than those computed at a point. Results of matching shots for a number of different scene types are illustrated on
منابع مشابه
Weak textured object recognition and localization using SESI
This paper approaches the problem of recognizing and localizing object with curved smooth and weak textured surfaces in a cluttered scene. In this work we present a new local invariant feature, SUSAN edgebased scale invariant feature (SESIF), to describe weak textured object, such as insulator, which is detected in a scalespace with scale selection. Different from several previous local invaria...
متن کاملA Sparse Texture Representation Using Affine-Invariant Regions
This paper introduces a texture representation suitable for recognizing images of textured surfaces under a wide range of transformations, including viewpoint changes and nonrigid deformations. At the feature extraction stage, a sparse set of affine-invariant local patches is extracted from the image. This spatial selection process permits the computation of characteristic scale and neighborhoo...
متن کاملContent-Based Image Retrieval Based on Local Affinely Invariant Regions
This contribution develops a new technique for content-based image retrieval. Where most existing image retrieval systems mainly focus on color and color distribution or texture, we classify the images based on local invariants. These features represent the image in a very compact way and allow fast comparison and feature matching with images in the database. Using local features makes the syst...
متن کاملDiscriminative Map Retrieval Using View-Dependent Map Descriptor
— Map retrieval, the problem of similarity search over a large collection of 2D pointset maps previously built by mobile robots, is crucial for autonomous navigation in indoor and outdoor environments. Bag-of-words (BoW) methods constitute a popular approach to map retrieval; however, these methods have extremely limited descriptive ability because they ignore the spatial layout information of ...
متن کاملVideo Google: A Text Retrieval Approach to Object Matching in Videos
We describe an approach to object and scene retrieval which searches for and localizes all the occurrences of a user outlined object in a video. The object is represented by a set of viewpoint invariant region descriptors so that recognition can proceed successfully despite changes in viewpoint, illumination and partial occlusion. The temporal continuity of the video within a shot is used to tr...
متن کامل