Event Retrieval Using Motion Barcodes

We introduce a simple and effective method for retrieval of videos showing a specific event, even when the videos of that event were captured from significantly different viewpoints. Appearance-based methods fail in such cases, as appearances change with large changes of viewpoints. Our method is based on a pixel-based feature, "motion barcode", which records the existence/non-existence of motion as a function of time. While appearance, motion magnitude, and motion direction can vary greatly between disparate viewpoints, the existence of motion is viewpoint invariant. Based on the motion barcode, a similarity measure is developed for videos of the same event taken from very different viewpoints. This measure is robust to occlusions common under different viewpoints, and can be computed efficiently. Event retrieval is demonstrated using challenging videos from stationary and hand held cameras

Camera Calibration from Dynamic Silhouettes Using Motion Barcodes

Computing the epipolar geometry between cameras with very different viewpoints is often problematic as matching points are hard to find. In these cases, it has been proposed to use information from dynamic objects in the scene for suggesting point and line correspondences. We propose a speed up of about two orders of magnitude, as well as an increase in robustness and accuracy, to methods computing epipolar geometry from dynamic silhouettes. This improvement is based on a new temporal signature: motion barcode for lines. Motion barcode is a binary temporal sequence for lines, indicating for each frame the existence of at least one foreground pixel on that line. The motion barcodes of two corresponding epipolar lines are very similar, so the search for corresponding epipolar lines can be limited only to lines having similar barcodes. The use of motion barcodes leads to increased speed, accuracy, and robustness in computing the epipolar geometry.Comment: Update metadat

An Epipolar Line from a Single Pixel

Computing the epipolar geometry from feature points between cameras with very different viewpoints is often error prone, as an object's appearance can vary greatly between images. For such cases, it has been shown that using motion extracted from video can achieve much better results than using a static image. This paper extends these earlier works based on the scene dynamics. In this paper we propose a new method to compute the epipolar geometry from a video stream, by exploiting the following observation: For a pixel p in Image A, all pixels corresponding to p in Image B are on the same epipolar line. Equivalently, the image of the line going through camera A's center and p is an epipolar line in B. Therefore, when cameras A and B are synchronized, the momentary images of two objects projecting to the same pixel, p, in camera A at times t1 and t2, lie on an epipolar line in camera B. Based on this observation we achieve fast and precise computation of epipolar lines. Calibrating cameras based on our method of finding epipolar lines is much faster and more robust than previous methods.Comment: WACV 201

The hunt for submarines in classical art: mappings between scientific invention and artistic interpretation

This is a report to the AHRC's ICT in Arts and Humanities Research Programme. This report stems from a project which aimed to produce a series of mappings between advanced imaging information and communications technologies (ICT) and needs within visual arts research. A secondary aim was to demonstrate the feasibility of a structured approach to establishing such mappings. The project was carried out over 2006, from January to December, by the visual arts centre of the Arts and Humanities Data Service (AHDS Visual Arts).1 It was funded by the Arts and Humanities Research Council (AHRC) as one of the Strategy Projects run under the aegis of its ICT in Arts and Humanities Research programme. The programme, which runs from October 2003 until September 2008, aims ‘to develop, promote and monitor the AHRC’s ICT strategy, and to build capacity nation-wide in the use of ICT for arts and humanities research’.2 As part of this, the Strategy Projects were intended to contribute to the programme in two ways: knowledge-gathering projects would inform the programme’s Fundamental Strategic Review of ICT, conducted for the AHRC in the second half of 2006, focusing ‘on critical strategic issues such as e-science and peer-review of digital resources’. Resource-development projects would ‘build tools and resources of broad relevance across the range of the AHRC’s academic subject disciplines’.3 This project fell into the knowledge-gathering strand. The project ran under the leadership of Dr Mike Pringle, Director, AHDS Visual Arts, and the day-to-day management of Polly Christie, Projects Manager, AHDS Visual Arts. The research was carried out by Dr Rupert Shepherd

The Evolution of First Person Vision Methods: A Survey

The emergence of new wearable technologies such as action cameras and smart-glasses has increased the interest of computer vision scientists in the First Person perspective. Nowadays, this field is attracting attention and investments of companies aiming to develop commercial devices with First Person Vision recording capabilities. Due to this interest, an increasing demand of methods to process these videos, possibly in real-time, is expected. Current approaches present a particular combinations of different image features and quantitative methods to accomplish specific objectives like object detection, activity recognition, user machine interaction and so on. This paper summarizes the evolution of the state of the art in First Person Vision video analysis between 1997 and 2014, highlighting, among others, most commonly used features, methods, challenges and opportunities within the field.Comment: First Person Vision, Egocentric Vision, Wearable Devices, Smart Glasses, Computer Vision, Video Analytics, Human-machine Interactio

The effects of "order" and "disorder" on human cognitive perception in navigating through urban environments

This paper investigates how “order”, “structure”, and “disorder” of street layouts are perceived when navigating through an urban environment. It builds on the assumption that a mixture of “order” and “disorder” might be a key factor for the quality of understanding within an urban context and that an “ordered” environment tends to be more intelligible when broken up by an irregularity occasionally. Knowledge about urban layouts can be accrued by the traveller in different ways: From static viewpoints, from top-down maps, and in travelling through the scenery. Cognitive processes that are involved in organising information about the structure of the built environment are known to simplify and schematise information. Such a “mental map” creates an image of the city, helps in memorising it and facilitates wayfinding tasks. Wayfinding experiments and investigations into the configuration of street networks have so far supported the understanding of movement behaviour and given insight from different perspectives on an urban environment. This paper will attempt to relate two aspects - configurational and sequential experiences of navigation (along a route) - to each other in using a methodological framework that allows for comparison of quantitative measurements and findings from both fields of research. The centre of attention will be the perception of “order”, “structure” and “disorder” from both perspectives: From “above” and from “along within” an urban environment. A virtual movement experiment with pre-chosen routes through six city samples is expected to provide meaningful empirical data with view on the perception of both configurational (view from above) and sequential (moving through scenery) embodiments of “order” and “disorder”, thereby introducing a methodological approach that applies string code computation in the spirit of probabilistic information theory