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Vision methods are very commonly used in underwater robotics. However, the cameras must be enclosed in a sealed housing for which flat-pane windows are the most economical and hence most popular solution. But they cause non-trivial refraction-based distortions at the air-glass-water interface. Recently, a new model for underwater cameras calibration called Pinax was introduced, which combines aspects...
A set of Matlab tools were developed to create seafloor mosaics from AUV photosurveys. The resulting mosaic products are used to guide instrument placement, ground-truth acoustic backscatter targets, and inspect sensor packages or other targets. Because of the positional sensitivity of these tasks, effort has been made to preserve the geographic distribution of the image content. After initial image...
Color mapping for 3D models with captured images is a classical problem in computer vision. Typically, registration between 3D model and images is assumed to be provided, otherwise corresponding points need to be labeled. For many applications, 3D model and images are acquired from different devices, since registration cannot be directly obtained, manual labeling has to be adopted. In this paper,...
The “Digital race — Driverless car” was a student competition where each team was given a model car with fixed specification in both mechanical and electronics. The mission was to program the car to run automatically in the condition of road having obstacles, missing lane lines and bridges with completely out lane lines in the field of view. This paper aims to address the issues facing in the competition...
Vision is a potent source of information, not just for humans, but for robots as well. Processing visual information is a computationally expensive task, one that is often difficult to accomplish in real-time on embedded hardware. In the broad field of visual research exists egomotion estimation, the process of determining self-motion from optical flow. Here we show a technological adaptation and...
Recovering 3D scene geometry from underwater images involves the Refractive Structure-from-Motion (RSfM) problem, where the image distortions caused by light refraction at the interface between different propagation media invalidates the single view point assumption. Direct use of the pinhole camera model in RSfM leads to inaccurate camera pose estimation and consequently drift. RSfM methods have...
Future of food innovation lies in the art and science of designing an interactive connected intelligent device that can detect how we feel and display the content suitable for individual consumers. We designed a smart dining table and chairs that can detect, sense, and analyze consumer's satisfaction, and interact with consumers. A team of furniture designer, software engineers, mechanical engineer,...
It is estimated that the number of devices connected to the Internet will be 50 billion by 2020. How should a not-so-tech-savvy end-user be able to discover, configure, and directly interact with a myriad of connected things in an intuitive and comfortable manner? Even if smartphones and wearables have shown potential for managing IoT environments, we cannot rely on that they can be used for all future...
In this paper, we propose a novel eye-tracking method that uses a multispectral camera to simultaneously track the pupil and recognize the iris. Our hybrid approach leverages existing methods, combining them so as to compensate for weaknesses present in each individual method when used alone. Significantly, our method allows for movements of the center of rotation of the eye to be taken into consideration,...
Current light field compression techniques lack robustness to handle both rate-distortion optimized motion compensation as well as latency during the encoding and decoding process. This paper focuses on a contribution approach that uses advanced frame prediction with affine and translational motion models and optimized view prediction structures. This method allows a significant compression performance...
This paper describes an industrial close-range photogrammetric system that is being developed by the authors. We describe the system's architecture based on an iterative scheme, which allows using fast heuristic point matching algorithms with the follow-up result verification. We also describe the design of our multi-functional coded targets that allow using those algorithms. Besides, this design...
Tangible User Interfaces (TUI) have garnered significant interest in the past years as a potential solution to embed smarter technologies for education. The intrinsic ability of this technology to engage and intrigue students in active learning pedagogies has recently been successfully proven across all ages using various techniques. Predominantly amongst the effective technologies, has been the development...
In this paper, we address the problem of person re-identification, which refers to associating the persons captured from different cameras. We propose a simple yet effective human part-aligned representation for handling the body part misalignment problem. Our approach decomposes the human body into regions (parts) which are discriminative for person matching, accordingly computes the representations...
This paper presents a novel strategy addressing visual SLAM with enhancement of data association method. Hyper graph theory and transformation was incorporated within cooperative visual SLAM. The research presented a synthetic approach to fulfill a cooperative data association and fusion strategy for multiple UAVs equipped with stereo vision cameras encountered with indistinct imaging, where conventional...
To watch 360° videos on normal 2D displays, we need to project the selected part of the 360° image onto the 2D display plane. In this paper, we propose a fully-automated framework for generating content-aware 2D normal-view perspective videos from 360° videos. Especially, we focus on the projection step preserving important image contents and reducing image distortion. Basically, our projection method...
Feature extraction and matching are two crucial components in person Re-Identification (ReID). The large pose deformations and the complex view variations exhibited by the captured person images significantly increase the difficulty of learning and matching of the features from person images. To overcome these difficulties, in this work we propose a Pose-driven Deep Convolutional (PDC) model to learn...
People detection in single 2D images has improved greatly in recent years. However, comparatively little of this progress has percolated into multi-camera multipeople tracking algorithms, whose performance still degrades severely when scenes become very crowded. In this work, we introduce a new architecture that combines Convolutional Neural Nets and Conditional Random Fields to explicitly model those...
Person Re-identification (re-id) aims to match people across non-overlapping camera views in a public space. It is a challenging problem because many people captured in surveillance videos wear similar clothes. Consequently, the differences in their appearance are often subtle and only detectable at the right location and scales. Existing re-id models, particularly the recently proposed deep learning...
An important challenge for autonomous robots is to navigate efficiently and safely in human populated environments. It requires that the robots perceive human motions and take into account human flows to plan and navigate. In this context we address the problem of modeling human flows from the perception of the robots, by defining a grid of the human motion likelihood over the environment, called...
This paper proposes a new background subtraction method by a moving camera for the object detection. Key points are firstly extracted and tracked. From the tracking results, spatial transformation relationships for the background scenes in consecutive frames are obtained while the current frame is warped to the previous image plane for the camera movement compensation. A codebook background model...
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