Real-time quality assessment of videos from body-worn cameras

Videos captured with body-worn cameras may be affected by distortions such as motion blur, overexposure and reduced contrast. Automated video quality assessment is therefore important prior to auto-tagging, event or object recognition, or automated editing. In this paper, we present M-BRISQUE, a spatial quality evaluator that combines, in real-time, the Michelson contrast with features from the Blind/Referenceless Image Spatial QUality Evaluator. To link the resulting quality score to human judgement, we train a Support Vector Regressor with Radial Basis Function kernel on the Computational and Subjective Image Quality database. We show an example of application of M-BRISQUE in automatic editing of multi-camera content using relative view quality, and validate its predictive performance with a subjective evaluation and two public datasets

Recording Victim Video Statements as Evidence to Advance Legal Outcomes in Family Violence Cases (ReVEAL)

This Implementation Guide provides an overview of the video-recording practices currently in place across several Texas jurisdictions. It provides guidance and considerations for jurisdictions in the collection and use of video evidence in family violence cases. This guide is divided into seven sections, including this Background and Overview. The second section includes information for law enforcement on the purpose of video statements, how to develop and implement a video program, and considerations for sustaining a program. The third section focuses on prosecutorial practices for the use of video statements including legal considerations, coordination with partners, and victim engagement around the video statement. The fourth section provides specific information for victim advocates and includes considerations for victim privacy and confidentiality. The fifth section focuses on technology and equipment, with information on type of equipment, technology infrastructure, and efficient transfer of evidence between agencies. The sixth section is the Summary Report of the ReVEAL project. The Summary Report is a technical overview of the evaluation that includes major findings and links to the ReVEAL reports that were previously released. The seventh and final section is comprised of the appendices and provides sample protocols, site overviews, equipment charts, and additional resources that may be helpful to users of this guide. Throughout this guide, there are several examples of cases and practices that illustrate the specific issues that may present themselves when launching a video-recording program. These examples highlight the complexities of the practice while using real world examples of how video impacts family violence cases, victim safety, and privacy.IC2 Institut

Analyzing the Use of Camera Glasses in the Wild

Camera glasses enable people to capture point-of-view videos using a common accessory, hands-free. In this paper, we investigate how, when, and why people used one such product: Spectacles. We conducted 39 semi-structured interviews and surveys with 191 owners of Spectacles. We found that the form factor elicits sustained usage behaviors, and opens opportunities for new use-cases and types of content captured. We provide a usage typology, and highlight societal and individual factors that influence the classification of behaviors.Comment: In Proceedings of the 37th Annual ACM Conference on Human Factors in Computing Systems (CHI 2019). ACM, New York, NY, US

Watching the Watchmen: Best Practices for Police Body Cameras

This paper examines the research on the costs and benefits of police body cameras, arguing that the devices can, if properly deployed and regulated, provide a valuable disincentive to police abuses as well as valuable evidence for punishing abuses when they occur

Applying psychological science to the CCTV review process: a review of cognitive and ergonomic literature

As CCTV cameras are used more and more often to increase security in communities, police are spending a larger proportion of their resources, including time, in processing CCTV images when investigating crimes that have occurred (Levesley & Martin, 2005; Nichols, 2001). As with all tasks, there are ways to approach this task that will facilitate performance and other approaches that will degrade performance, either by increasing errors or by unnecessarily prolonging the process. A clearer understanding of psychological factors influencing the effectiveness of footage review will facilitate future training in best practice with respect to the review of CCTV footage. The goal of this report is to provide such understanding by reviewing research on footage review, research on related tasks that require similar skills, and experimental laboratory research about the cognitive skills underpinning the task. The report is organised to address five challenges to effectiveness of CCTV review: the effects of the degraded nature of CCTV footage, distractions and interrupts, the length of the task, inappropriate mindset, and variability in people’s abilities and experience. Recommendations for optimising CCTV footage review include (1) doing a cognitive task analysis to increase understanding of the ways in which performance might be limited, (2) exploiting technology advances to maximise the perceptual quality of the footage (3) training people to improve the flexibility of their mindset as they perceive and interpret the images seen, (4) monitoring performance either on an ongoing basis, by using psychophysiological measures of alertness, or periodically, by testing screeners’ ability to find evidence in footage developed for such testing, and (5) evaluating the relevance of possible selection tests to screen effective from ineffective screener

The Effect of Police Body-Worn Cameras on Use of Force and Citizens’ Complaints Against the Police: A Randomized Controlled Trial

Objective: Police use-of-force continues to be a major source of international concern, inviting interest by academics and practitioners alike. Whether justified or unnecessary/excessive, the exercise of power by the police can potentially tarnish their relationship with the community. Police misconduct can translate into complaints against the police, which carry large economic and social costs. The question we try to answer is: do body-worn-cameras reduce the prevalence of use-of-force and/or citizens’ complaints against the police? Methods: We empirically tested the use of body-worn-cameras by measuring the effect of videotaping police-public encounters on incidents of police use-of-force and complaints, in randomized-controlled settings. Over 12 months, we randomly-assigned officers to “experimental-shifts” during which they were equipped with body-worn HD cameras that recorded all contacts with the public and to “control-shifts” without the cameras (n=988). We nominally defined use-of-force, both unnecessary/excessive and reasonable, as a non-desirable response in police-public encounters. We estimate the causal effect of the use of body-worn-videos on the two outcome variables using both between-group differences using a Poisson regression model as well as before-after estimates using interrupted time-series analyses. Results: We found that the likelihood of force being used in control conditions were roughly twice those in experimental conditions. Similarly, a pre/post analysis of use-of-force and complaints data also support this result: the number of complaints filed against officers dropped from 0.7 complaints per 1,000 contacts to 0.07 per 1,000 contacts. We discuss the findings in terms of theory, research methods, policy and future avenues of research on body-worn-videos.Funding for this research was granted by Rialto Police and the Jerry Lee Centre of Experimental CriminologyThis is the accepted manuscript. The final publication is available at Springer via http://dx.doi.org/10.1007/s10940-014-9236-3

Improving Sequential Determinantal Point Processes for Supervised Video Summarization

It is now much easier than ever before to produce videos. While the ubiquitous video data is a great source for information discovery and extraction, the computational challenges are unparalleled. Automatically summarizing the videos has become a substantial need for browsing, searching, and indexing visual content. This paper is in the vein of supervised video summarization using sequential determinantal point process (SeqDPP), which models diversity by a probabilistic distribution. We improve this model in two folds. In terms of learning, we propose a large-margin algorithm to address the exposure bias problem in SeqDPP. In terms of modeling, we design a new probabilistic distribution such that, when it is integrated into SeqDPP, the resulting model accepts user input about the expected length of the summary. Moreover, we also significantly extend a popular video summarization dataset by 1) more egocentric videos, 2) dense user annotations, and 3) a refined evaluation scheme. We conduct extensive experiments on this dataset (about 60 hours of videos in total) and compare our approach to several competitive baselines