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This paper presents the evaluation of visual features for the proposed two eye detection method applied to thermal images. The use of two eye region is due to its distinctive pattern and to overcome the issue of blurred and noisy characteristic in the thermal image. Comparative performance analysis on three different features which includes Haar, Histogram of Oriented Gradients (HoG) and Local Binary...
This paper describes a component of an Augmented Reality (AR) based system focused on supporting workers in manufacturing and maintenance industry. Particularly, it describes a component responsible for verification of performed steps. Correct handling is crucial in both manufacturing and maintenance industries and deviations may cause problems in later stages of the production and assembly. The primary...
The performance of local descriptors such as SIFT drops under severe illumination changes. In this paper, we propose a Discriminative and Contrast Invertible (DCI) local feature descriptor. In order to increase the discriminative ability of the descriptor under illumination changes, a Laplace gradient based histogram is proposed. Moreover, a robust contrast flipping estimate is proposed based on the...
This paper proposes a new approach for image classification by combining pyramid match kernel(PMK) with spatial pyramid. Unlike the conventional spatial pyramid matching (SPM) approach which only uses a single-resolution feature vector to represent an image, we use a multi-resolution feature vector to represent an image for SPM. We then calculate the match scores at each resolution of SPM representation...
This paper addresses the problem of automatic target recognition (ATR) using inverse synthetic aperture radar (ISAR) images. In this context, we propose a novel approach for feature extraction to describe precisely an aircraft target from ISAR images. In our approach, a visual attention model is adopted to separate the salient regions from the background. After that, the scale invariant feature transform...
SIMPLE (Searching Images with MPEG-7 (& MPEG-7-like) Powered Localized dEscriptors) is a model that proposes the reuse of well-established global descriptors by localizing their description mechanism on image patches located by local features' detectors. Having displayed impressive retrieval results on two different databases, in this paper we extend the family by replacing the originally picked...
Smile detection in the wild is an interesting and challenging problem. This paper presents an efficient approach with hierarchical visual feature to handle this problem. In our approach, Gabor filters with multi-scale, multi-orientation are first applied to extract facial textures namely Gabor faces from the input face image. After this, Histograms of Oriented Gradients (HOG) are employed to encode...
This paper addresses the problem of aggregating local binary descriptors for large scale image retrieval in mobile scenarios. Binary descriptors are becoming increasingly popular, especially in mobile applications, as they deliver high matching speed, have a small memory footprint and are fast to extract. However, little research has been done on how to efficiently aggregate binary descriptors. Direct...
Correct recognition of emotion veracity exhibited in facial gestures is troublesome for people. Yet, there is a belief that computer systems are able to perceive some tiny changes correlated to veracity expression, invisible for people, and therefore are able to improve proper perception of emotions. This work addresses the problem of spontaneous and posed smile recognition and suggests two approaches...
Twitter is currently the most popular tool for social interaction and real-time information exchange. Outreach and importance of individual accounts is measured by the number of their followers. The aim of this paper is to investigate the applicability and usefulness of corpora containing textual and visual information for the purpose of machine observation of Twitter activities. The results in the...
The current paper suggests an initial segmentation system, detection and grouping of visual information based on faces to facilitate the use, the handling and validation of the VIDTIMIT database. In order to implement this basis, two methods of pretreatment for each face are used. Then faces are detected with the Viola and Jones algorithm based on weak type descriptors Haar and grouped by new faces...
Identifying different types of damage is very essential in times of natural disasters, where first responders are flooding the internet with often annotated images and texts, and rescue teams are overwhelmed to prioritize often scarce resources. While most of the efforts in such humanitarian situations rely heavily on human labor and input, we propose in this paper a novel hybrid approach to help...
This paper proposes a new Spatial Pyramid representation approach for image classification. Unlike the conventional Spatial Pyramid, the proposed method is invariant to rotation changes in the images. This method works by partitioning an image into concentric rectangles and organizing them into a pyramid. Each pyramidal region is then represented using a histogram of visual words. Our experimental...
Object tracking is one of the most important topics in computer vision. While the state-of-the-art tracking algorithms achieved great success, there are still some challenging problems to be solved. Firstly, it remains a tough task to develop a tracking algorithm with both accuracy and efficiency. Secondly, the ground truth is often given by a rectangular bounding box, which contains not only the...
Personalized and content-adaptive image enhancement can find many applications in the age of social media and mobile computing. This paper presents a relative-learning-based approach, which, unlike previous methods, does not require matching original and enhanced images for training. This allows the use of massive online photo collections to train a ranking model for improved enhancement. We first...
Fashion is a major segment in e-commerce with growing importance and a steadily increasing number of products. Since manual annotation of apparel items is very tedious, the product databases need to be organized automatically, e.g. by image classification. Common image classification approaches are based on features engineered for general purposes which perform poorly on specific images of apparel...
A mathematical morphology based filter structure called a sieve is used to process mouth image sequences of a talker's mouth and form visual speech features. The effects of varying the type of filter, the post-processing and hidden Markov model (HMM) parameters on recognition accuracy are investigated using two audio-visual speech databases.
Due to the increasing popularity of location-based services, the need for reliable and cost-effective indoor positioning methods is rising. As an alternative to radio-based localization methods, in 2011, we introduced MoVIPS (Mobile Visual Indoor Positioning System), which is based on the idea to extract visual feature points from a query image and compare them to those of previously collected geo-referenced...
The human brain receives images from the natural world and understands scenes, places and events quickly, outperforming the most advanced artificial vision system. Most of surfaces are textured in real life. Thus, In this paper, a novel texture analysis method has been proposed. The texture can be seen as a visual representation of complex patterns that lead to cognitive understanding of the environment...
Perceptual quality evaluation of the retargeting image plays an important role in benchmarking different retargeting methods, as well as guiding or optimizing the retargeting process. The distortions introduced during the retargeting process are mainly categorized into shape distortion and content information loss [1]. The shape distortion measurement is critical to the evaluation of retargeting image...
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