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This paper presents a novel approach, named bag-of-bags of words (BBoW), to address the problem of Content-Based Image Retrieval (CBIR) from image databases. The proposed bag-of-bags of words model extends the classical bag-of-words (BoW) model. An image is represented as a connected graph of local features on a regular grid. Then irregular partitions (subgraphs) of images are further built via Normalized...
Classification of the content of a scanned document as either printed or handwritten is typically tackled as a segmentation problem of pages into text lines or words. However these methods are not applicable on documents where handwritten annotations overlay printed text. In this paper we propose to treat the task as a pixel classification task, i.e., To classify individual foreground pixels into...
A novel distinctive descriptor named MSOGH is proposed, which is able to well represent the interest region and is robust to photometric transformations and geometric transformations. According to intensity order, subregions are firstly constructed. Then feature descriptor of the subregion is computed by point permutation of the sample points in each subregion. Finally, feature descriptor of the region...
In this paper we propose a novel method for shape analysis called HTS (Hough Transform Statistics), which uses statistics from Hough Transform space in order to characterize the shape of objects in digital images. Experimental results showed that the HTS descriptor is robust and presents better accuracy than some traditional shape description methods. Furthermore, HTS algorithm has linear complexity,...
Many applications of machine learning involve analysis of sparse high-dimensional data, where the number of input features is larger than the number of data samples. Standard classification methods may not be sufficient for such data, and this provides motivation for non-standard learning settings. One such new learning methodology is called Learning through Contradictions or Universum support vector...
With the existing feature weighting methods of image retrieval field, it was impossible to use the fact that images have different key features depending on their classes because the same weight is applied to every image class. We propose a method of indexing features of each class in order of importance and giving them relevant weights, which can be applied to image retrieval. We designed a simple...
The pedestrian detection literature has been recently extended by the availability of large-scale multisensory datasets, able to capture complementary aspects of the objects of interest, namely, appearance, motion, and depth. In this paper, we exploit this multimodal scenario to propose a new set of composite descriptors dubbed CO2, CO-variances of visual features and CO-occurrences of depth fields...
In the field of computer vision, pyramid matching by minimization has gained increasing popularity. This paper points out and discusses an inherent anomaly in pyramid matching by minimization that can affect the performance of classification approaches based on this type of matching. As a solution, a new multiresolution measure, called Manhattan-Pyramid Distance (MPD), is proposed. Systematic evaluations...
Design of video storyboards has emerged as a popular research area in the multimedia community. Different pattern clustering techniques are applied to extract the key frames from a video sequence to form a storyboard. In this paper, we propose an automatic method for the selection of key frames of a video sequence using Delaunay graphs. We prune certain edges from the Delaunay graph using an iterative...
The conventional EM algorithms may suffer from the following two problems. First, it may converge to a local maximum. Second, the algorithm may suffer from singularity. A novel Enhanced EM algorithm (EEM) using a realization of maximum-entropy uniform distribution as initial condition is proposed. A global optimal solution can be obtained. In addition, a positive perturbation scheme is adopted to...
Pedestrian detection is an important feature in an advanced, automated video surveillance system. Unfortunately in most situations cameras are mounted in a way that, due to perspective, walking humans are occluded by each other or stationary objects and detecting a whole silhouette is not possible. But heads and shoulders are not occluded in most cases and can be used for object classification (human...
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