Precise motion descriptors extraction from stereoscopic footage using DaVinci DM6446

A novel approach to extract target motion descriptors in multi-camera video surveillance systems is presented. Using two static surveillance cameras with partially overlapped field of view (FOV), control points (unique points from each camera) are identified in regions of interest (ROI) from both cameras footage. The control points within the ROI are matched for correspondence and a meshed Euclidean distance based signature is computed. A depth map is estimated using disparity of each control pair and the ROI is graded into number of regions with the help of relative depth information of the control points. The graded regions of different depths will help calculate accurately the pace of the moving target and also its 3D location. The advantage of estimating a depth map for background static control points over depth map of the target itself is its accuracy and robustness to outliers. The performance of the algorithm is evaluated in the paper using several test sequences. Implementation issues of the algorithm onto the TI DaVinci DM6446 platform are considered in the paper

Estimating commitment in a digital market place environment

The future generation of mobile communication shall be a convergence of mobile telephony and information systems which promises to change people's lives by enabling them to access information when, where and how they want. It presents opportunities to offer multimedia applications and services that meet end-toend service requirements. The Digital Marketplace framework will enable users to have separate contracts for different services on a per call basis. In order for such a framework to function appropriately, there has to be some means for the network operator to know in advance if its network will be able to support the user requirements. This paper discusses the methods by which the network operator will be able to determine if the system will be able to support another user of a certain service class and therefore negotiate parameters like commitment, QoS and the associated cost for providing the service, thus making the Digital Marketplace wor

Echolocation detections and digital video surveys provide reliable estimates of the relative density of harbour porpoises

Acknowledgements We would like to thank Erik Rexstad and Rob Williams for useful reviews of this manuscript. The collection of visual and acoustic data was funded by the UK Department of Energy & Climate Change, the Scottish Government, Collaborative Offshore Wind Research into the Environment (COWRIE) and Oil & Gas UK. Digital aerial surveys were funded by Moray Offshore Renewables Ltd and additional funding for analysis of the combined datasets was provided by Marine Scotland. Collaboration between the University of Aberdeen and Marine Scotland was supported by MarCRF. We thank colleagues at the University of Aberdeen, Moray First Marine, NERI, Hi-Def Aerial Surveying Ltd and Ravenair for essential support in the field, particularly Tim Barton, Bill Ruck, Rasmus Nielson and Dave Rutter. Thanks also to Andy Webb, David Borchers, Len Thomas, Kelly McLeod, David L. Miller, Dinara Sadykova and Thomas Cornulier for advice on survey design and statistical approache. Data Accessibility Data are available from the Dryad Digital Repository: http://dx.doi.org/10.5061/dryad.cf04gPeer reviewedPublisher PD

In-loop Feature Tracking for Structure and Motion with Out-of-core Optimization

In this paper, a novel and approach for obtaining 3D models from video sequences captured with hand-held cameras is addressed. We define a pipeline that robustly deals with different types of sequences and acquiring devices. Our system follows a divide and conquer approach: after a frame decimation that pre-conditions the input sequence, the video is split into short-length clips. This allows to parallelize the reconstruction step which translates into a reduction in the amount of computational resources required. The short length of the clips allows an intensive search for the best solution at each step of reconstruction which robustifies the system. The process of feature tracking is embedded within the reconstruction loop for each clip as opposed to other approaches. A final registration step, merges all the processed clips to the same coordinate fram

Exploring the reliability of the modified Rankin Scale

<p><b>Background and Purpose:</b> The modified Rankin Scale (mRS) is the most prevalent outcome measure in stroke trials. Use of the mRS may be hampered by variability in grading. Previous estimates of the properties of the mRS have used diverse methodologies and may not apply to contemporary trial populations. We used a mock clinical trial design to explore inter- and intraobserver variability of the mRS.</p> <p><b>Methods:</b> Consenting patients with stroke attending for outpatient review had the mRS performed by 2 independent assessors with pairs of assessors selected from a team of 3 research nurses and 4 stroke physicians. Before formal assessment, interviewers estimated disability based only on initial patient observation. Each patient was then randomized to undergo the mRS using standard assessment or a prespecified structured interview. The second interviewer in the pair reassessed the patient using the same method blinded to the colleague’s score. For each patient assessed, one rater was randomly assigned to video record their interview. After 3 months, this interviewer reviewed and regraded their original video assessment.</p> <p><b>Results:</b> Across 100 paired assessments, interobserver agreement was moderate (k=0.57). Intraobserver variability was good (k=0.72) but less than would be expected from previous literature. Forty-nine assessments were performed using the structured interview approach with no significant difference between structured and standard mRS. Researchers were unable to reliably predict mRS from initial limited patient assessment (k=0.16).</p> <p><b>Conclusions:</b> Despite availability of training and structured interview, there remains substantial interobserver variability in mRS grades awarded even by experienced researchers. Additional methods to improve mRS reliability are required.</p&gt

Object-based 2D-to-3D video conversion for effective stereoscopic content generation in 3D-TV applications

Three-dimensional television (3D-TV) has gained increasing popularity in the broadcasting domain, as it enables enhanced viewing experiences in comparison to conventional two-dimensional (2D) TV. However, its application has been constrained due to the lack of essential contents, i.e., stereoscopic videos. To alleviate such content shortage, an economical and practical solution is to reuse the huge media resources that are available in monoscopic 2D and convert them to stereoscopic 3D. Although stereoscopic video can be generated from monoscopic sequences using depth measurements extracted from cues like focus blur, motion and size, the quality of the resulting video may be poor as such measurements are usually arbitrarily defined and appear inconsistent with the real scenes. To help solve this problem, a novel method for object-based stereoscopic video generation is proposed which features i) optical-flow based occlusion reasoning in determining depth ordinal, ii) object segmentation using improved region-growing from masks of determined depth layers, and iii) a hybrid depth estimation scheme using content-based matching (inside a small library of true stereo image pairs) and depth-ordinal based regularization. Comprehensive experiments have validated the effectiveness of our proposed 2D-to-3D conversion method in generating stereoscopic videos of consistent depth measurements for 3D-TV applications