Argonauta Video Database: Spectography experiment. Scene 3 (Right camera)

Scenes for Spectrography experiment Scenes were recorded following the tasks involved in spectrography experiments, which are carried out in front of "J9" output radiadion channel, the latter in open condition. These tasks may be executed by one or two persons. One person can do the tasks, but requiring him to crouch in front of "J9" to adjust the angular position the experimental appartus (a crystal to bend the neutron radiation to the spectograph), and then to get up to verify data in a computer aside; these movements are repeated until achieving the right operational conditions. Two people may aid one another in such a way one remais crouched while the other remains still in front of the computer. They may also interchange tasks so as to divide received doses. Up to now, there are available two scenes with one person and one scene with two persons. These scenes are described in the sequel: - Scene 3: Comprises the scene with two persons performing spectography experiment. Video file labels: "20140327182905_IPCAM": recorded by the right camera.

Argonauta Video Database: Spectography experiment. Scene 3 (Left camera)

Scenes for Spectrography experiment Scenes were recorded following the tasks involved in spectrography experiments, which are carried out in front of "J9" output radiadion channel, the latter in open condition. These tasks may be executed by one or two persons. One person can do the tasks, but requiring him to crouch in front of "J9" to adjust the angular position the experimental appartus (a crystal to bend the neutron radiation to the spectograph), and then to get up to verify data in a computer aside; these movements are repeated until achieving the right operational conditions. Two people may aid one another in such a way one remais crouched while the other remains still in front of the computer. They may also interchange tasks so as to divide received doses. Up to now, there are available two scenes with one person and one scene with two persons. These scenes are described in the sequel: - Scene 3: Comprises the scene with two persons performing spectography experiment. Video file labels: "20140327182906_IPCAM": recorded by the left camera.

Argonauta Video Database: General simulated. Scene 2 (Left camera)

General simulated scenes These scenes followed a pre-defined script (see the Thesis for details), with common movements corresponding to general experiments. People go to or stand still in front of "J9", and/or go to the side of Argonauta reactor and come back again. The first type of movement is common during Irradiation experiments, where a material sample is put within the "J9" channel; and also during neutrongraphy or gammagraphy experiments, where a sample is placed in front of "J9". Here, the detailed movements of putting samples on these places were not reproduced in details, but only the whole bodies' movements were simulated (as crouching or being still in front of "J9"). The second type of movement may occur when operators go to the side of Argonauta to verify some operational condition. - Scene 2: Comprises one of the scenes with two persons. Both of them use clothes of dark colors. Both persons go to the side of Argonauta reactor and then come back and go out. Video file labels: "20140326154755_IPCAM": recorded by the left camera.

Argonauta Video Database: Real operation. Scene 1 (Right camera)

Real operation scene This scene was recorded during a real Irradiation operation, more specifically during its final tasks (removing the irradiated sample). This scene was an extra recording to the script and planned ones. - Scene: Involved a number of persons, as: two operators, two personnel belonging to the radiological protection service, and the "client" who asked for the irradiation. Video file labels: "20140402150657_IPCAM": recorded by the right camera.

Argonauta Video Database: Real operation. Scene 1 (Left camera)

Real operation scene This scene was recorded during a real Irradiation operation, more specifically during its final tasks (removing the irradiated sample). This scene was an extra recording to the script and planned ones. - Scene: Involved a number of persons, as: two operators, two personnel belonging to the radiological protection service, and the "client" who asked for the irradiation. Video file labels: "20140402150658_IPCAM": recorded by the left camera.

Argonauta Video Database: Projection and Homography matrices. Projection Left Camera

Description of the Annotation files: Annotation files are supplied for each video, for benchmarking. Annotations correspond to ground truths of peoples' positions in the image plane, and also for their feet positions, when they were visible. Annotations were performed manually, with the aid of a code developed by (Silva et al., 2014; see the Thesis for details). Targets (people or feet) are marked at variable frame intervals and then linearly interpolated.

Argonauta Video Database: Projection and Homography matrices. Projection Right Camera

Description of the Annotation files: Annotation files are supplied for each video, for benchmarking. Annotations correspond to ground truths of peoples' positions in the image plane, and also for their feet positions, when they were visible. Annotations were performed manually, with the aid of a code developed by (Silva et al., 2014; see the Thesis for details). Targets (people or feet) are marked at variable frame intervals and then linearly interpolated.

Argonauta Video Database: Projection and Homography matrices. Homography Right Camera

Description of the Annotation files: Annotation files are supplied for each video, for benchmarking. Annotations correspond to ground truths of peoples' positions in the image plane, and also for their feet positions, when they were visible. Annotations were performed manually, with the aid of a code developed by (Silva et al., 2014; see the Thesis for details). Targets (people or feet) are marked at variable frame intervals and then linearly interpolated.

Argonauta Video Database: Projection and Homography matrices. Homography Left Camera

Description of the Annotation files: Annotation files are supplied for each video, for benchmarking. Annotations correspond to ground truths of peoples' positions in the image plane, and also for their feet positions, when they were visible. Annotations were performed manually, with the aid of a code developed by (Silva et al., 2014; see the Thesis for details). Targets (people or feet) are marked at variable frame intervals and then linearly interpolated.

Argonauta Video Database. Data Agregation

This Database was generated during the development of a computer vision-based system for safety purposes in nuclear plants. The system aims at detecting and tracking people within a nuclear plant. Further details may be found in the related thesis. The research was developed through a cooperation between the Graduate Electrical Engineering Program of Federal University of Rio de Janeiro (PEE/COPPE, UFRJ) and the Nuclear Engineering Institute of National Commission of Nuclear Energy (IEN, CNEN). The experimental part of this research was carried out in Argonauta, a nuclear research reactor belonging to IEN. The Database is made available in the sequel. All the videos are already rectified. The Projection and Homography matrices are given in the end, for both cameras. Please, acknowledge the use of this Database in any publication.

Compression Efficiency Analysis of Wyner-Ziv Video Coding with Motion Compensated Side Information Interpolation

The Wyner-Ziv video coding (WZVC) rate distortion performance is highly dependent on the quality of the side information, an estimation of the original frame, created at the decoder. This paper, characterizes the WZVC efficiency when motion compensated frame interpolation (MCFI) techniques are used to generate the side information, a difficult problem in WZVC especially because the decoder only has available some reference decoded frames. The proposed WZVC compression efficiency rate model relates the power spectral of the estimation error to the accuracy of the MCFI motion field. Then, some interesting conclusions may be derived related to the impact of the motion field smoothness and the correlation to the true motion trajectories on the compression performance.

Low Complexity Intra Mode Selection for Efficient Distributed Video Coding

Motion compensated frame interpolation (MCFI) is one of the most efficient solutions to generate side information (SI) in the context of distributed video coding. However, it creates SI with rather significant motion compensated errors for some frame regions while rather small for some other regions depending on the video content. In this paper, a low complexity Infra mode selection algorithm is proposed to select the most 'critical' blocks in the WZ frame and help the decoder with some reliable data for those blocks. For each block, the novel coding mode selection algorithm estimates the encoding rate for the Intra based and WZ coding modes and determines the best coding mode while maintaining a low encoder complexity. The proposed solution is evaluated in terms of rate-distortion performance with improvements up to 1.2 dB regarding a WZ coding mode only solution.

Advanced side information creation techniques and framework for Wyner-Ziv video coding

Recently, several distributed video coding (DVC) solutions based on the distributed source coding (DSC) paradigm have appeared in the literature. Wyner-Ziv (WZ) video coding, a particular case of DVC where side information is made available at the decoder, enable to achieve a flexible distribution of the computational complexity between the encoder and decoder, promising to fulfill novel requirements from applications such as video surveillance, sensor networks and mobile camera phones. The quality of the side information at the decoder has a critical role in determining the WZ video coding rate-distortion (RD) performance, notably to raise it to a level as close as possible to the RD performance of standard predictive video coding schemes. Towards this target, efficient motion search algorithms for powerful frame interpolation are much needed at the decoder. In this paper, the RD performance of a Wyner-Ziv video codec is improved by using novel, advanced motion compensated frame interpolation techniques to generate the side information. The development of these type of side information estimators is a difficult problem in WZ video coding, especially because the decoder only has available some reference, decoded frames. Based on the regularization of the motion field, novel side information creation techniques are proposed in this paper along with a new frame interpolation framework able to generate higher quality side information at the decoder. To illustrate the RD performance improvements, this novel side information creation framework has been integrated in a transform domain turbo coding based Wyner-Ziv video codec. Experimental results show that the novel side information creation solution leads to better RD performance than available state-of-the-art side information estimators, with improvements up to 2 dB: moreover, it allows outperforming H.264/AVC Intra by up to 3 dB with a lower encoding complexity.

Personalised placement in networked video

Personalised video can be achieved by inserting objects into a video play-out according to the viewer's profile. Content which has been authored and produced for general broadcast can take on additional commercial service features when personalised either for individual viewers or for groups of viewers participating in entertainment, training, gaming or informational activities. Although several scenarios and use-cases can be envisaged, we are focussed on the application of personalised product placement. Targeted advertising and product placement are currently garnering intense interest in the commercial networked media industries. Personalisation of product placement is a relevant and timely service for next generation online marketing and advertising and for many other revenue generating interactive services. This paper discusses the acquisition and insertion of media objects into a TV video play-out stream where the objects are determined by the profile of the viewer. The technology is based on MPEG-4 standards using object based video and MPEG-7 for metadata. No proprietary technology or protocol is proposed. To trade the objects into the video play-out, a Software-as-a-Service brokerage platform based on intelligent agent technology is adopted. Agencies, libraries and service providers are represented in a commercial negotiation to facilitate the contractual selection and usage of objects to be inserted into the video play-out.

Behind video lectures in a MOOC

The year 2012 was the “boom year” in MOOC and all its outstanding growth until now, made us move forward in designing the first MOOC in our Institution (and the third in our country, Portugal). Most MOOC are video lectured based and the learning analytic process to these ones is just taking its first steps. Designing a video-lecture seems, at a first glance, very easy: one can just record a live lesson or lecture and turn it, directly, into a video-lecture (even here one may experience some “sound” and “camera” problems); but developing some engaging, appealing video-lecture, that motivates students to embrace knowledge and that really contributes to the teaching/learning process, it is not an easy task. Therefore questions like: “What kind of information can induce knowledge construction, in a video-lecture?”, “How can a professor interact in a video-lecture when he is not really there?”, “What are the video-lectures attributes that contribute the most to viewer’s engagement?”, “What seems to be the maximum “time-resistance” of a viewer?”, and many others, raised in our minds when designing video-lectures to a Mathematics MOOC from the scratch. We believe this technological resource can be a powerful tool to enhance students' learning process. Students that were born in digital/image era, respond and react slightly different to outside stimulus, than their teachers/professors ever did or do. In this article we will describe just how we have tried to overcome some of the difficulties and challenges we tackled when producing our own video-math-lectures and in what way, we feel, videos can contribute to the teaching and learning process at higher education level.