Vision and Violence in Virginia Woolf’s The Waves

Virginia Woolf describes her artistic goal in The Waves as an attempt to create “an abstract mystical eyeless book.” Yet, in creating her eyeless book, one that eschews a single narrative perspective, Woolf amasses abundant visual details. For each of her six characters, visual images mark significant moments of being. In fact, Woolf emphasizes the characters’ capacity for sight as a vulnerability that allows them to be violated and wounded over and over. This article analyzes connections between visual imagery and themes of violence in the novel to demonstrate how they cohere into an extended metaphor for the ways in which acts of looking can elicit powerful emotions that threaten to fragment individual identity in painful ways. While Woolf’s novel has received critical commentary that focuses on the role of vision in the narrative and critics have also noted how violence in the text supports other themes, the explicit relationship between sight and violence has not yet been fully explored. A close examination of the visual imagery in key scenes of the novel demonstrates how Woolf engages the reader to participate in the characters’ deepening sense of fragmentation as they are repeatedly assaulted by experience, as the eyes themselves become symbols of the twin dynamics of desire and destruction

Multiple Object Tracking in Urban Traffic Scenes with a Multiclass Object Detector

Multiple object tracking (MOT) in urban traffic aims to produce the trajectories of the different road users that move across the field of view with different directions and speeds and that can have varying appearances and sizes. Occlusions and interactions among the different objects are expected and common due to the nature of urban road traffic. In this work, a tracking framework employing classification label information from a deep learning detection approach is used for associating the different objects, in addition to object position and appearances. We want to investigate the performance of a modern multiclass object detector for the MOT task in traffic scenes. Results show that the object labels improve tracking performance, but that the output of object detectors are not always reliable.Comment: 13th International Symposium on Visual Computing (ISVC

A spatially distributed model for foreground segmentation

Foreground segmentation is a fundamental first processing stage for vision systems which monitor real-world activity. In this paper we consider the problem of achieving robust segmentation in scenes where the appearance of the background varies unpredictably over time. Variations may be caused by processes such as moving water, or foliage moved by wind, and typically degrade the performance of standard per-pixel background models. Our proposed approach addresses this problem by modeling homogeneous regions of scene pixels as an adaptive mixture of Gaussians in color and space. Model components are used to represent both the scene background and moving foreground objects. Newly observed pixel values are probabilistically classified, such that the spatial variance of the model components supports correct classification even when the background appearance is significantly distorted. We evaluate our method over several challenging video sequences, and compare our results with both per-pixel and Markov Random Field based models. Our results show the effectiveness of our approach in reducing incorrect classifications

Electric Shadows (Dianying) *

Catalogue Essay on Isaac Julien's installation "Ten Thousand Waves". Probably also included in catalogue for Isaac Julien exhibition Sao Paulo Autumn 201

Improving Multiple Object Tracking with Optical Flow and Edge Preprocessing

In this paper, we present a new method for detecting road users in an urban environment which leads to an improvement in multiple object tracking. Our method takes as an input a foreground image and improves the object detection and segmentation. This new image can be used as an input to trackers that use foreground blobs from background subtraction. The first step is to create foreground images for all the frames in an urban video. Then, starting from the original blobs of the foreground image, we merge the blobs that are close to one another and that have similar optical flow. The next step is extracting the edges of the different objects to detect multiple objects that might be very close (and be merged in the same blob) and to adjust the size of the original blobs. At the same time, we use the optical flow to detect occlusion of objects that are moving in opposite directions. Finally, we make a decision on which information we keep in order to construct a new foreground image with blobs that can be used for tracking. The system is validated on four videos of an urban traffic dataset. Our method improves the recall and precision metrics for the object detection task compared to the vanilla background subtraction method and improves the CLEAR MOT metrics in the tracking tasks for most videos

Seeing is Believing : The Capacity of the Manipulated Photograph to Represent Scenes of Mythology and the Supernatural

This illustrated paper explores the capacity of the manipulated photograph to represent scenes of mythology and the supernatural. Can a photograph, which is said to be an index of the real, render a mythical realm into a believable scene? Practices such a double exposures and combination printing have historically been used to create famous faked images of the supernatural, such as the Cottingley Fairy images and Spurgen’s photograph of the Loch Ness monster. The photograph has a causal link with reality and as such a carefully manipulated image has the power to deceive or persuade the viewer. In her photography project ‘Realm’ Carolyn Lefley explores this apparent truth-telling phenomenon by constructing double exposure photographs that create a layering of realities. A familiar domestic interior and a potentially mythological landscape combine to create scenes of make-believe, which reference texts such as Alice in Wonderland and The Lion, The Witch and the Wardrobe. Down the rabbit hole, through the looking glass and into the wardrobe, all of these paths lead from the realm of the real, into the realm of myth. The kingdom of Narnia is entered through an ordinary wardrobe. The photograph of a homely interior becomes a portal into a mythical realm. The idea of creating fictional realms and in essence writing new mythology is a practice known as mythopoeia, which fascinated authors such as JRR Tolkien, CS Lewis and George MacDonald. The photographs in ‘Realm’ depict new image-worlds of myth and wonder. Post-production techniques have been utilised to achieve these images. The paper will conclude with a consideration of the next era in photography, that of computer simulated reality. Sarah Kember notes in her book Virtual Anxiety that the veracity of the photograph is not threatened by this paradigm shift, suggesting that any representation only constructs an ‘image-idea’ of reality.Non peer reviewedFinal Accepted Versio