Maintenance of digital image libraries requires to frequently asses the quality of the images to engage preservation measures if necessary. We present an approach to image based quality assurance for digital image collections based on local descriptor matching. We use spatially distinctive local keypoints of contrast enhanced images and robust symmetric descriptor matching to calculate affine t...

The paper presents a novel, theoretically well-based methodology to find changes in remote sensing image series. The proposed method finds changes in images scanned with a long time-interval difference in very different lighting and surface conditions. The presented method is basically an exploitation of the Harris saliency function and its derivatives for finding featuring points among image s...

Recent years have seen a lot of work on local descriptors. In all published comparisons or evaluations, the now quite well-known SIFT-descriptor has been one of the top performers. For the application of object pose estimation, one comparison showed a local descriptor, called the Patch-Duplet, of equal or better performance than SIFT. This paper examines different properties of those two descri...

Li proposed a novel generative/discriminative way to combine features with different types and use them to learn labels in the images. However, the mixture of Gaussian used in Li’s paper sufferes greatly from the curse of dimensionality. Here I propose an alternative approach to generate local region descriptor. I treat GMM with diagonal covariance matrix and PCA as separate features, and combi...

We propose a novel local nearest neighbor distance (LNND) descriptor for anomaly detection in crowded scenes. Comparing with the commonly used low-level feature descriptors in previous works, LNND descriptor has two major advantages. First, LNND descriptor efficiently incorporates spatial and temporal contextual information around the video event that is important for detecting anomalous intera...

In this paper we propose to tackle human actions indexing by introducing a new local motion descriptor. Our proposed descriptor is based on two modeling, a spatial model and a temporal model. The spatial model is computed by projection of optical flow onto bivariate orthogonal polynomials. Then, the time evolution of spatial coefficients is modeled with a one dimension polynomial basis. To perf...

In this paper we present an algorithm for face detection that is based on generic local descriptors (e.g. eyes). A generic descriptor captures the distribution of individual descriptors over a set of samples (training images). This distribution is assumed to be a Gaussian mixture model and is learnt using the minimum description length principle (MDL). A descriptor of an unknown image may then ...

We present a novel semi-local image descriptor which encodes multiple edges corresponding to the image structure boundaries around an interest point. The proposed method addresses the problem of poor edge detection through a robust, scale and orientation invariant, descriptor distance. In addition, a clustering of descriptors capable of extracting distinctive shapes from a set of descriptors is...

A novel local structure descriptor (LSD) for color image retrieval is proposed in this paper. Local structures are defined based on a similarity of edge orientation, and LSD is constructed using the underlying colors in local structures with similar edge direction. LSD can effectively combine color, texture and shape as a whole for image retrieval. LSH integrates the advantages of both statisti...