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Drone-based aerial thermography has become a convenient quality assessment tool for the precise localization of defective modules and cells in large photovoltaic-power plants. However, manual evaluation of aerial infrared recordings can be extremely time-consuming. Therefore, we propose an approach for automatic detection and analysis of photovoltaic modules in aerial infrared images. Significant...
In the study on sports image classification, the characteristics of human pose increasingly raise concerns of researchers. However, the same posture for human may be resulted from different scenes and scene objects that express diverse action states and meanings. Thus, combination of human pose and event scenes shall be considered so as to improve performance of sports image classification. In recent...
We compare the performance of three segmentation algorithms, initially developed by the team to extract the blood vessel network in fundus images of infant retina, on publicly available data sets. We envisage to parametrize any data-dependent factor (such as thresholds) to adapt to the data set. Experimental results show that through the proposed supervised-learning approach to tune parameters, all...
In robot perception, as well as in other areas of 3-D computer vision, keypoint detection is the first major step for an efficient and accurate 3-D perception of the environment. Thus, a fast and robust algorithm for an automatic identification of keypoints in unstructured 3-D point clouds is essential. The presented algorithm is designed to be highly parallelizable and can be implemented on modern...
Affective computing has become a growing field of research activities due to its wide use of application in human computer interface. Emotion recognition is one of the state-of-the-art techniques in determining current psychological state of human being. Human emotions are very overlapping in nature and thus it needs an efficient feature-extractor and classifier assembly. This paper reports a novel...
Automatic vegetation coverage detection plays a key role for monitoring and management of land usage, environmental variation, and urban planning. This paper presents a novel vegetation coverage detection technique for very high resolution multi-spectral satellite imagery. The proposed technique consists of two stages including a supervised patch-level scoring stage and an unsupervised pixel-level...
The cross-depiction problem is that of recognising visual objects regardless of whether they are photographed, painted, drawn, etc. It introduces great challenge as the variance across photo and art domains is much larger than either alone. We extensively evaluate classification, domain adaptation and detection benchmarks for leading techniques, demonstrating that none perform consistently well given...
The study investigates the accuracy and precision of the proposed system by cross examining the values solved using the proposed system with the values solved manually. Since the feature extractor and classifier directly influences the accuracy and precision of Optical Character Recognition, the study considered choosing the top of the line combination of Feature Extractor-Classifier combination for...
In this document an algorithm is proposed to identify the state (available/occupied) of the parking spaces in outdoor areas. The algorithm was developed based on two features: the average local entropy, and the standard deviation of the average entropies of subregions of each parking space. The algorithm delivers a binary map, which contains the number of each parking space with its attributes such...
Pooled steganalysis combines evidence from multiple objects to achieve higher accuracy in detecting hidden messages at the expense of granularity, as the decision is provided on the set of objects instead of a single one. Although it has been introduced almost decade ago, very little work has been done since then. This work builds upon recent advances in machine learning to show, how an optimal function...
Different contacts between objects afford different interactions between them. For example, while contacts below an object can provide support, contacts on opposing sides can be used for pinching. Hence, a robot can learn to predict which interactions are currently afforded based on the set of contacts. However, representing sets of contacts is not trivial, as the number of contacts is not fixed nor...
Enhanced Local Ternary Patterns (ELTP) significantly improves performance over other feature descriptor methods including Local Binary Patterns (LBP) and Local Ternary Patterns (LTP).Sequential implementation of ELTP results in poor performance in terms of execution time for real time systems.Speed and accuracy are important characteristics of a real time face recognition system. With the aim of fulfilling...
This paper presents an automatic event detection system fusing low and mid level features for soccer videos. We first employ an improved approach for Shot Boundary Detection with color and our mean-gradient feature. Then we classify the shots into two view types. We also perform a template-based replay detection for each shot. Play-break sequences are then generated using a rule-based method. We devise...
In this work, a method is proposed for classification of texture images using a fusion of feature sets. Weighted guided filter based preprocessing technique has been performed using optimized cost function to enhance the discriminative property of different texture images. A hybrid model of normalized symmetrical gray level co-occurrence matrix parameters, histogram of oriented gradients, and Gabor...
Classification of high-resolution remote-sensing images is a challenging research area. In this paper we proposed a novel decision fusion framework to combine bag of features (BOF) based classifiers. The proposed framework, can also be used in multi category image classification applications. A single voting algorithm is used for decision fusion and an ambiguity detection module is used to determine...
This paper proposes an efficient tracking method to handle the appearance of object. Distribution fields descriptor (DF) which allows the representation of uncertainty about the tracked object has been proved to be very robust to illumination changes, image noise and small misalignments. However, DF tracking is a generative model that does not utilize the background information, which limits its discriminative...
The Spatial Pyramid Matching approach has become very popular to model images as sets of local bag-of-words. The image comparison is then done region-by-region with an intersection kernel. Despite its success, this model presents some limitations: the grid partitioning is predefined and identical for all images and the matching is sensitive to intra- and inter-class variations. In this paper, we propose...
Human action recognition based on joints is a challenging task. The 3D positions of the tracked joints are very noisy if occlusions occur, which increases the intra-class variations in the actions. In this paper, we propose a novel approach to recognize human actions with weighted joint-based features. Previous work has focused on hand-tuned joint-based features, which are difficult and time-consuming...
his article presents a novel systematic methodology for the detection of interest points in 3D point clouds and its corresponding descriptors by using the information of an RGB camera and a structured-light sensor. This is achieved by fusing Speeded-Up Robust Features (SURF) in the image space, and histograms that statistically represent the relationship of three dimensional geometric data around...
Although a great success has been achieved on action detection tasks by using "bag of features" architecture as video representations, action detection with web camera still remains a challenge. Most of these algorithms can extract features either sparsely at interest points or densely on regular grids, usually, sampling densely can get better results than sampling sparsely using the local...
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