Summarizing First-Person Videos from Third Persons' Points of Views

Video highlight or summarization is among interesting topics in computer vision, which benefits a variety of applications like viewing, searching, or storage. However, most existing studies rely on training data of third-person videos, which cannot easily generalize to highlight the first-person ones. With the goal of deriving an effective model to summarize first-person videos, we propose a novel deep neural network architecture for describing and discriminating vital spatiotemporal information across videos with different points of view. Our proposed model is realized in a semi-supervised setting, in which fully annotated third-person videos, unlabeled first-person videos, and a small number of annotated first-person ones are presented during training. In our experiments, qualitative and quantitative evaluations on both benchmarks and our collected first-person video datasets are presented.Comment: 16+10 pages, ECCV 201

Ego-Downward and Ambient Video based Person Location Association

Using an ego-centric camera to do localization and tracking is highly needed for urban navigation and indoor assistive system when GPS is not available or not accurate enough. The traditional hand-designed feature tracking and estimation approach would fail without visible features. Recently, there are several works exploring to use context features to do localization. However, all of these suffer severe accuracy loss if given no visual context information. To provide a possible solution to this problem, this paper proposes a camera system with both ego-downward and third-static view to perform localization and tracking in a learning approach. Besides, we also proposed a novel action and motion verification model for cross-view verification and localization. We performed comparative experiments based on our collected dataset which considers the same dressing, gender, and background diversity. Results indicate that the proposed model can achieve $18.32 \%$ improvement in accuracy performance. Eventually, we tested the model on multi-people scenarios and obtained an average $67.767 \%$ accuracy

Lifestyle understanding through the analysis of egocentric photo-streams

At 8:15, before going to work, Rose puts on her pullover and attaches to it the small portable camera that looks like a hanger. The camera will take two images per minute throughout the day and will record almost everything Rose experiences: the people she meets, how long she sits in front of her computer, what she eats, where she goes, etc. These images show an objective description of Rose's experiences. This thesis addresses the development of automatic computer vision tools for the study of people's behaviours. To this end, we rely on the analysis of the visual data offered by these collected sequences of images by wearable cameras. Our developed models have demonstrated to be a powerful tool for the extraction of information about the behaviours of people in society. Examples of applications: 1) selected images as cues to trigger autobiographical memory about past events for prevention of cognitive and functional decline and memory enhancement in elderly people. 2) Self-monitoring devices as people want to increase their self-knowledge through quantitative analysis, expecting that it will lead to psychological well-being and the improvement of their lifestyle. 3) businesses are already making use of such data regarding information about their employees and clients, in order to improve productivity, well-being and customer satisfaction. The ultimate goal is to help people like Rose to improve the quality of our life by creating awareness about our habits and life balance

(Not So) Innocent Bystander: The Embodied Views of the Body Camera

As police brutality cases have become more discussed over the past several years, there have been many debates surrounding the police body camera, but thus far, little research has been done on the body camera’s relation to semiotics and phenomenology. Through an analysis of the body camera’s indexicality and embodiment, this thesis aims to dismantle the argument often proposed by law enforcement that the body camera is a purely observatory, evidential piece of technology. To best identify the complications that the body camera presents, the thesis compares three different instances where body camera footage was released to the public and how each set of footage functions