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In this paper, we propose a new method for customized summarization of egocentric videos according to specific user preferences, so that different users can extract different summaries from the same stream. Our approach, tailored on a cultural heritage scenario, relies on creating a short synopsis of the original video focused on key shots, in which concepts relevant to user preferences can be visually...
Computer vision systems are designed to work well within the context of everyday photography. However, artists often render the world around them in ways that do not resemble photographs. Artwork produced by people is not constrained to mimic the physical world, making it more challenging for machines to recognize.,,This work is a step toward teaching machines how to categorize images in ways that...
"STAT (U) ES" is an interactive art that enables a subjective experience of site-specificity using projectionmapping and facial recognition system. This work consists of two parts, a camera part that captures facial images and a projection part where an image of the Buddhist Sculpture is projected on wooden boxes. A viewer is first instructed to read the caption of the work and the facial...
The purpose of this study is learning and classification of video activities using video color and motion information. The video activity labeling is important for many applications such as video content modeling, indexing, and quick access to content. In this study video activity recognition is performed by deep learning. In order to learn visual features of video, Convolutional Neural Network (CNN)...
Human actions recognition has been one of the most popular subject areas in computer vision. Recently, the usage of depth cameras which are capable of generating three dimensional data enabled more complex human actions to be recognized. In this study, the problem of tennis actions recognition using a depth camera is tackled and a three dimensional tennis actions dataset has been created. To be able...
Stereo Match is one of the key fields in computer vision. Although many dense two-frame stereo algorithms have been developed in this domain, few utilize cross check and disparity gradient based refinement method. This paper proposes: (1) Cross check method using two generated disparity maps based on left and right original images. (2) A novel occluded and low-texture region growth method based on...
Deep learning architectures have shown great success in various computer vision applications. In this study, we investigate some of the very popular convolutional neural network (CNN) architectures, namely GoogleNet, AlexNet, VGG19 and ResNet. Furthermore, we show possible early feature fusion strategies for visual object classification tasks. Concatanation of features, average pooling and maximum...
In this study, the automated matching of 2.5 m resolution Göktürk-2 panchromatic stereo images has been addressed. From an operational perspective, it seems unlikely to produce the epipolar images from Göktürk-2 stereo datasets at a sub-pixel level due to several reasons. Therefore, SIFT-flow method that does not require any user input and that has ability to perform matching through the stereo data...
Visual Saliency Estimation is a computer vision problem that aims to find the regions of interest that are frequently in eye focus in a scene or an image. Since most computer vision problems require discarding irrelevant regions in a scene, visual saliency estimation can be used as a preprocessing step in such problems. In this work, we propose a method to solve top-down saliency estimation problem...
Today, trying to understand what kind of behaviour the crowd shows by studying the data from surveillance systems is an important topic for researchers of computer vision. The aim of this study make the motion data that is at pixel level and that is obtained by optical flow method a more meaningful data set with the particle advection method. In other words, the aim is to monitor the motion data by...
In this paper, the comparison of a novel key-point image descriptors such as DAISY, BRISK, A-KAZE and LATCH with the well-known SIFT and SURF descriptors are tested and compared for the stereo matching algorithm. The main idea of this paper is to present an independent, comparative study and some of the benefits and drawbacks of these most popular image descriptors on stereo images. These descriptors...
In the past few years, the number of fine-art collections that are digitized and publicly available has been growing rapidly. With the availability of such large collections of digitized artworks comes the need to develop multimedia systems to archive and retrieve this pool of data. Measuring the visual similarity between artistic items is an essential step for such multimedia systems, which can benefit...
In computer vision, gradient-based tracking is usually performed from monochromatic inputs. However, few researches consider the influence of the chosen colorto- grayscale conversion technique. This paper evaluates the impact of these conversion algorithms on tracking and homography calculation results, both being fundamental steps of augmented reality applications. Eighteen color-togreyscale algorithms...
The usage of computer vision applications such as 3D reconstruction, motion tracking and augmented reality gradually increases. The first and the most important stage of these kind of applications is esitimating the 3D scene model and motion information. We developed an easy-to-use user interface in order to use in these kind of applications. The user interface we developed, contains important functionalities...
In this study, in order to obtain similar effect with conventional gradient operation and extract more robust feature for texture, we use the principal curvature informations instead of the gradient calculation. Through this methods, sharp and important informations about the texture images were obtained by analyzing images of the second order. Considering the classification results obtained, it is...
A novel low complexity feature extraction algorithm, only performing by a single comparison per pixel on the average during detection is proposed. While single-scale version of the algorithm remains quite efficient compared against the complexity of the state-of-the-art algorithms, a multi-scale version is also proposed to handle blur and scale changes. The performance tests on the repeatability of...
In this work we are presenting a sparse disparity map extraction procedure based on block matching approach. The blocks are taken around the edge locations in the reference image and searched in the target image by evaluating matching costs for each search location. For this block matching approach, the performances of cost calculation methods, such as Sum of Absolute Differences (SAD), Herman Weyl's...
This work collects the explorations conducted within the EPFL+ECAL Lab by several designers to interpret the various spheres of action of Augmented Reality in order to derive visual principles. These principles seek to contribute to developing a specific visual grammar, which is essential if Augmented Reality is to go beyond technological performance to acquire the status of a true media, like all...
lifeClipper3 is a media art project in which a walk is audiovisually expanded into a game-like experience by means of “augmented reality” technologies. For visitors this creates an immersive experience which is unique in each case, and which challenges and calls into question habitual modes of perception. In this paper the “experience design” strategies used in lifeClipper3 are introduced, and examined...
This study is an experimental attempt to construct a comprehensive archive of signature elements of Korean modern painters, Park Sugeun and Chun Kyungja, through image-base-danalysis of their artworks in order to provide scientific criteria for connoisseurship. The artists' signature elements derived from biological and psychological models of human visual system were then applied to authentication...
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