High Order Structure Descriptors for Scene Images
Structure information is ubiquitous in natural scene images and it plays an important role in scene representation. In this paper, third order structure statistics (TOSS) and fourth order structure statistics (FOSS) are exploited to encode higher order structure information. Afterwards, based on the radial and normal slice of TOSS and FOSS, we propose the high order structure feature: third order structure feature (TOSF) and fourth order structure feature (FOSF). It is well known that scene images are well characterized by particular arrangements of their local structures, we divide the scene image into the non-overlapping sub-regions and compute the proposed higher order structural features among them. Then a scene classification is performed by using SVM classifier with these higher order structure features. The experimental results show that higher order structure statistics can deliver image structure information well and its spatial envelope has strong discriminative ability.
Code (0)
등록된 구현이 없습니다.
Tasks
Scene ClassificationVocal Bursts Intensity PredictionSimilar Papers 제목 키워드 기반
Fast Dictionary Matching for Content-based Image Retrieval
This paper describes a method for searching for common sets of descriptors between collections of images. The presented method operates on local interest keypoints, which are generated using the SURF algorithm. The use o…
Content-Based Image RetrievalImage RetrievalRetrievalPUMP: Pyramidal and Uniqueness Matching Priors for Unsupervised Learning of Local Descriptors
Existing approaches for learning local image descriptors have shown remarkable achievements in a wide range of geometric tasks. However, most of them require per-pixel correspondence-level supervision, which is diffi…
Visual LocalizationHigher order PCA-like rotation-invariant features for detailed shape descriptors modulo rotation
PCA can be used for rotation invariant features, describing a shape with its $p_{ab}=E[(x_i-E[x_a])(x_b-E[x_b])]$ covariance matrix approximating shape by ellipsoid, allowing for rotation invariants like its traces of po…
Scene UnderstandingObject RecognitionImproved Descriptors for Patch Matching and Reconstruction
We propose a convolutional neural network (ConvNet) based approach for learning local image descriptors which can be used for significantly improved patch matching and 3D reconstructions. A multi-resolution ConvNet is us…
3D ReconstructionPatch MatchingCrowd Source Scene Change Detection and Local Map Update
As scene changes with time map descriptors become outdated, affecting VPS localization accuracy. In this work, we propose an approach to detect structural and texture scene changes to be followed by map update. In our me…
Change DetectionScene Change Detection