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Autonomous robots performing various tasks without human guidance have always been our dream for a better future. A problem that faces autonomous robots is dealing with novel situations. One of the recent technologies that has proven its ability to deal with such situation is Brain-Based Device(BBD). However, the large computational power needed to simulate its nervous system is a major limitation...
Human's everyday environment is an open environment in which objects with new shapes, colors or textures frequently appear. Enabling robots to deal with such environments and to manipulate those objects raises a difficult challenge: how to recognize an object? How to distinguish it from the background? An approach is proposed here to allow the robot to find this segmentation on its own. It relies...
Human Activity detection is an imperative area of research in computer vision. This paper focuses on activity recognition by construction personnel at the construction sites. The method uses bag of features (BOF) approach to detect an activity. Here we have considered five types of activities done at construction sites namely ladder climbing, brick laying, carpentry work, painting and plastering work...
Due to the advancement in multimedia technology, the images and videos play a major role in day today life. How the humans are looking into the image? The computational models of visual attention used in many of the computer vision tasks such as image segmentation, object recognition, image understanding, etc. The proposed method aims to construct visual saliency model with the help of the center...
In this paper, a work in progress towards a real-time vision-based traffic flow prediction (TFP) system is resented. The proposed method consists of three elemental operators, that are dynamic texture model based motion segmentation, feature extraction and Gaussian process (GP) regression. The objective of motion segmentation is to recognize the target regions covering the moving vehicles in the sequence...
This paper presents an unsupervised visual theme discovery framework as a better (more compact and effective) alternative for semantic representation of visual contents. Firstly, a tag filtering algorithm was proposed focusing on the tag’s ability of visual content description. Then a spectral clustering algorithm is applied to cluster tags into visual themes based on their visual similarity...
First-person action recognition is a recent problem in computer vision, where an observer wears body cameras to understand and recognize actions from the captured video sequences. Technological advances have made it possible to offer small wearable cameras that can be attached onto bike helmets, belts, animal halters, among other accessories. Examples of potential applications include sports, security,...
A variety of methods have been proposed for object level saliency detection, which is useful for many content-based computer vision applications. Unlike most previous work that integrate multiple low level cues to compute the saliency map, this paper presents a novel hierarchical optimization model. First, we compute a rough saliency map using HS method, and then, boundary and foreground seeds are...
Vision is vital to decision making, as humans naturally trust their eyes to enhance situation awareness. Yet the modern age has overwhelmed humans with massive amounts of visual information, which is problematic in time sensitive and mission critical situations, such as emergency management and disaster response. More efficient search and retrieval systems address some of these issues, which is why...
Most objects are designed for certain functionalities. For example, a knife is designed for cutting, and a hammer for pounding. Indeed, functionalities are not related to the objects themselves but to certain object parts, e.g., the blade of a knife affords cutting. A part can have different shapes and can exist in different objects such as a scraper or a peeler, but it carries the same functional...
The blind spot of software testing is the assessment of the actual behavior of the system under test in the real, physical world. In this paper we show how this inherent restriction of software testing to the "cyber world" can be overcome with the use of methods and techniques from computer vision. It augments conventional software testing and allows making observations about states and...
While the abundance of visual content available on the Internet, and the easy access to such content by all users allows us to find relevant content quickly, it also poses challenges. For example, if a parent wants to restrict the visual content which their child can see, this content needs to either be automatically tagged as offensive or not, or a computer vision algorithm needs to be trained to...
Every day the popularity of 3D printing is growing. It is used in almost all fields of the modern science and techniques. Applications of this technology is widespread: from architecture and design, to Biomedicine and aerospace. Despite its popularity, the process of additive 3D printing usually takes a while. During this process we need to be sure that the printed object stays static, besides, we...
On-going progressions of Information Technology increase the scope for computer vision-based interventions to facilitate efficient and promising technology for people with disabilities. This project aims to develop a wearable navigational assistive device, titled EyeVista, to facilitate visually impaired sprint athletes. It is a lightweight, easy-to-use, customizable and low-cost wearable jacket built-in...
Human activity recognition in video camera is the prime research topic in computer vision and machine learning since last many years. Visual cameras have been used in public and private place like railway station, shopping malls, airport, offices, schools and university, etc. to recognize threat in the scene. The automated visual surveillance system will help to catch suspect in the scene, person...
Human action recognition from videos has wide applicability and receives significant interests. In this work, to better identify spatio-temporal characteristics, we propose a novel 3D extension of Gradient Location and Orientation Histograms, which provides discriminative local features representing not only the gradient orientation, but also their relative locations. We further propose a human action...
Given a user wearing a low frame rate wearable camera during a day, this work aims to automatically detect the moments when the user gets engaged into a social interaction solely by reviewing the automatically captured photos by the worn camera. The proposed method, inspired by the sociological concept of F-formation, exploits distance and orientation of the appearing individuals -with respect to...
Inferring the aesthetic quality of images is a challenging computer vision task due to its subjective and conceptual nature. Most image aesthetics evaluation approaches focused on designing handcrafted features, and only a few adopted learning of relevant and imperative characteristics in a data-driven manner. In this paper, we propose to attune Convolutional Neural Networks (CNNs) for image aesthetics...
This paper proposes a critical survey of crowd analysis techniques using visual and non-visual sensors. Automatic crowd understanding has a massive impact on several applications including surveillance and security, situation awareness, crowd management, public space design, intelligent and virtual environments. In case of emergency, it enables practical safety applications by identifying crowd situational...
Nonverbal cues constitute a significant part of human communication. Traditionally the object of psychology, nonverbal communication studies now permeate fields such as social signal processing and human computer interaction. The ubiquity of digital recordings of human social interactions and of free sharing platforms offers many opportunities for the automated analysis of group interaction dynamics;...
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