We address the problem of finding deformation between two images for the purpose of recognizing objects. The challenge is that discriminative features are often transformation-variant (e.g. histogram of oriented gradients, texture), while transformation-invariant features (e.g. intensity, color) are often not discriminative. We introduce the concept of attribute flow which explicitly models how...

Despite the ubiquitous use of distance transforms in the shape analysis literature and the popularity of fast marching and fast sweeping methods—essentially HamiltonJacobi solvers, there is very little recent work leveraging the Hamilton-Jacobi to Schrödinger connection for representational and computational purposes. In this work, we exploit the linearity of the Schrödinger equation to (i) des...

This paper addresses the challenge of establishing a bridge between deep convolutional neural networks and conventional object detection frameworks for accurate and efficient generic object detection. We introduce Dense Neural Patterns, short for DNPs, which are dense local features derived from discriminatively trained deep convolutional neural networks. DNPs can be easily plugged into convent...

Cervical cancer is one of the most common types of cancer in women worldwide. Most deaths of cervical cancer occur in less developed areas of the world. In this work, we introduce a new image dataset along with ground truth diagnosis for evaluating image-based cervical disease classification algorithms. We collect a large number of cervigram images from a database provided by the US National Ca...

Automatic machine reading of texts in scenes is largely restricted by the poor character recognition accuracy. In this paper, we extend the Histogram of Oriented Gradient (HOG) and propose two new feature descriptors: Cooccurrence HOG (Co-HOG) and Convolutional Co-HOG (ConvCo-HOG) for accurate recognition of scene texts of different languages. Compared with HOG which counts orientation frequenc...

Video recording of construction operations provides an understandable data that could be used to analyze and improve construction performance. Despite the benefits, manual stopwatch study of previously recorded videos can be laborintensive, may suffer from biases of the observers, and impractical after substantial period of observations. To address these limitations, this paper presents a new v...

Considered as among the most thriving applications in the pattern recognition field, handwriting recognition, despite being quite matured, it still raises so many research questions which are a challenge for the Arabic Handwritten Script. In this paper, we investigate Support Vector Machines (SVM) for Arabic Handwritten Script recognition. The proposed method takes the handcrafted feature as in...

Automatic detection and classification of pollen species has value for use inside of palynologic allergen studies. Traditional labeling of different pollen species requires an expert biologist to classify particles by sight, and is therefore time-consuming and expensive. Here, an automatic process is developed which segments the particle contour and uses the extracted features for the classific...

In face recognition, face rotation alignment is an important part of the recognition process. In this paper, we present a hierarchical detector system using eye and eye-pair detectors combined with a geometrical method for calculating the in-plane angle of a face image. Two feature extraction methods, the restricted Boltzmann machine and the histogram of oriented gradients, are compared to extr...

This paper emphasised an approach for offline signature verification and identification. Two image descriptors are studied, including Pyramid Histogram of Oriented Gradients (PHOG), and a direction feature proposed in the literature. Compared with many previously proposed signature feature extraction approaches, PHOG has advantages in the extraction of discriminative information from handwritin...