Kutalmis Akpinar, Trevor Ballard, K. Hua, Kai Li, Sansiri Tarnpradab, Jun Ye
We present COMMIT (Collaborative MultiMedia Interactive Table), a collaborative multimedia environment for remote group interaction. COMMIT enables collaboration among people at different locations by allowing them to not only share multimedia objects such as images, PDFs and videos, but also co-operate on these cyber objects. COMMIT is also motivated by the emerging Internet of Things (IoT), and provides a team-thing interface which supports the sharing of data streams from physical IoT objects, such as IP cameras. It enables collaborators to more effectively exploit huge volumes of valuable IoT data. COMMIT has been evaluated using real-life scenarios with random users. Feedback from our user study shows that COMMIT is intuitive and can aid group interactions in collaborative tasks requiring the Internet of Things.
{"title":"COMMIT: A Multimedia Collaboration System for Future Workplaces with the Internet of Things","authors":"Kutalmis Akpinar, Trevor Ballard, K. Hua, Kai Li, Sansiri Tarnpradab, Jun Ye","doi":"10.1145/3083187.3084022","DOIUrl":"https://doi.org/10.1145/3083187.3084022","url":null,"abstract":"We present COMMIT (Collaborative MultiMedia Interactive Table), a collaborative multimedia environment for remote group interaction. COMMIT enables collaboration among people at different locations by allowing them to not only share multimedia objects such as images, PDFs and videos, but also co-operate on these cyber objects. COMMIT is also motivated by the emerging Internet of Things (IoT), and provides a team-thing interface which supports the sharing of data streams from physical IoT objects, such as IP cameras. It enables collaborators to more effectively exploit huge volumes of valuable IoT data. COMMIT has been evaluated using real-life scenarios with random users. Feedback from our user study shows that COMMIT is intuitive and can aid group interactions in collaborative tasks requiring the Internet of Things.","PeriodicalId":123321,"journal":{"name":"Proceedings of the 8th ACM on Multimedia Systems Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129809341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes a novel High Efficiency Video Coding (HEVC) Tile partitioning method for parallel processing by analyzing the computing ability of asymmetric multicores. The proposed method (i) analyzes the computing ability of asymmetric multicores and (ii) makes a regression model of computational complexity per video resolutions. Finally, the model (iii) determines the optimal HEVC Tile resolution for each core and partitions/allocates the Tiles to suitable cores.; AB@The proposed method minimizes the decoding time gap between faster CPU cores and power-efficient cores (big/LITTLE cores). Experimental results with 4K ultra-high definition (UHD) test sequences show an average improvement of 25% in decoding speed for most recent Android smart phones.
{"title":"Video on Mobile CPU: UHD Video Parallel Decoding for Asymmetric Multicores","authors":"Yeongil Ryu, Eun‐Seok Ryu","doi":"10.1145/3083187.3083229","DOIUrl":"https://doi.org/10.1145/3083187.3083229","url":null,"abstract":"This paper proposes a novel High Efficiency Video Coding (HEVC) Tile partitioning method for parallel processing by analyzing the computing ability of asymmetric multicores. The proposed method (i) analyzes the computing ability of asymmetric multicores and (ii) makes a regression model of computational complexity per video resolutions. Finally, the model (iii) determines the optimal HEVC Tile resolution for each core and partitions/allocates the Tiles to suitable cores.; AB@The proposed method minimizes the decoding time gap between faster CPU cores and power-efficient cores (big/LITTLE cores). Experimental results with 4K ultra-high definition (UHD) test sequences show an average improvement of 25% in decoding speed for most recent Android smart phones.","PeriodicalId":123321,"journal":{"name":"Proceedings of the 8th ACM on Multimedia Systems Conference","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114228867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
State-of-the-art Software Defined Wide Area Networks (SD-WANs) provide the foundation for flexible and highly resilient networking. In this work we design, implement and evaluate a novel architecture (denoted SABR) that leverages the benefits of SDN to provide network assisted Adaptive Bitrate Streaming. With clients retaining full control of their streaming algorithms we clearly show that by this network assistance, both the clients and the content providers benefit significantly in terms of QoE and content origin offloading. SABR utilizes information on available bandwidths per link and network cache contents to guide video streaming clients with the goal of improving the viewer's QoE. In addition, SABR uses SDN capabilities to dynamically program flows to optimize the utilization of CDN caches.; AB@Backed by our study of SDN assisted streaming we discuss the change in the requirements for network-to-player APIs that enables flexible video streaming. We illustrate the difficulty of the problem and the impact of SDN-assisted streaming on QoE metrics using various well established player algorithms. We evaluate SABR together with state-of-the-art DASH quality adaptation algorithms through a series of experiments performed on a real-world, SDN-enabled testbed network with minimal modifications to an existing DASH client. Our measurements show the substantial improvement in cache hitrates in conjunction with SABR indicating a rich design space for jointly optimized SDN-assisted caching architectures for video streaming applications.
{"title":"Network Assisted Content Distribution for Adaptive Bitrate Video Streaming","authors":"Divyashri Bhat, Amr Rizk, M. Zink, R. Steinmetz","doi":"10.1145/3083187.3083196","DOIUrl":"https://doi.org/10.1145/3083187.3083196","url":null,"abstract":"State-of-the-art Software Defined Wide Area Networks (SD-WANs) provide the foundation for flexible and highly resilient networking. In this work we design, implement and evaluate a novel architecture (denoted SABR) that leverages the benefits of SDN to provide network assisted Adaptive Bitrate Streaming. With clients retaining full control of their streaming algorithms we clearly show that by this network assistance, both the clients and the content providers benefit significantly in terms of QoE and content origin offloading. SABR utilizes information on available bandwidths per link and network cache contents to guide video streaming clients with the goal of improving the viewer's QoE. In addition, SABR uses SDN capabilities to dynamically program flows to optimize the utilization of CDN caches.; AB@Backed by our study of SDN assisted streaming we discuss the change in the requirements for network-to-player APIs that enables flexible video streaming. We illustrate the difficulty of the problem and the impact of SDN-assisted streaming on QoE metrics using various well established player algorithms. We evaluate SABR together with state-of-the-art DASH quality adaptation algorithms through a series of experiments performed on a real-world, SDN-enabled testbed network with minimal modifications to an existing DASH client. Our measurements show the substantial improvement in cache hitrates in conjunction with SABR indicating a rich design space for jointly optimized SDN-assisted caching architectures for video streaming applications.","PeriodicalId":123321,"journal":{"name":"Proceedings of the 8th ACM on Multimedia Systems Conference","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121641315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Surveillance devices with IP addresses are accessible on the Internet and play a crucial role in monitoring physical worlds. Discovering surveillance devices is a prerequisite for ensuring high availability, reliability, and security of these devices. However, today's device search depends on keywords of packet head fields, and keyword collection is done manually, which requires enormous human efforts and induces inevitable human errors. The difficulty of keeping keywords complete and updated has severely impeded an accurate and large-scale device discovery. To address this problem, we propose to automatically generate device fingerprints based on webpages embedded in surveillance devices. We use natural language processing to extract the content of webpages and machine learning to build a classification model. We achieve real-time and non-intrusive web crawling by leveraging network scanning technology. We implement a prototype of our proposed discovery system and evaluate its effectiveness through real-world experiments. The experimental results show that those automatically generated fingerprints yield very high accuracy of 99% precision and 96% recall. We also deploy the prototype system on Amazon EC2 and search surveillance devices in the whole IPv4 space (nearly 4 billion). The number of devices we found is almost 1.6 million, about twice as many as those using commercial search engines.
{"title":"Automatically Discovering Surveillance Devices in the Cyberspace","authors":"Qiang Li, Xuan Feng, Haining Wang, Limin Sun","doi":"10.1145/3083187.3084020","DOIUrl":"https://doi.org/10.1145/3083187.3084020","url":null,"abstract":"Surveillance devices with IP addresses are accessible on the Internet and play a crucial role in monitoring physical worlds. Discovering surveillance devices is a prerequisite for ensuring high availability, reliability, and security of these devices. However, today's device search depends on keywords of packet head fields, and keyword collection is done manually, which requires enormous human efforts and induces inevitable human errors. The difficulty of keeping keywords complete and updated has severely impeded an accurate and large-scale device discovery. To address this problem, we propose to automatically generate device fingerprints based on webpages embedded in surveillance devices. We use natural language processing to extract the content of webpages and machine learning to build a classification model. We achieve real-time and non-intrusive web crawling by leveraging network scanning technology. We implement a prototype of our proposed discovery system and evaluate its effectiveness through real-world experiments. The experimental results show that those automatically generated fingerprints yield very high accuracy of 99% precision and 96% recall. We also deploy the prototype system on Amazon EC2 and search surveillance devices in the whole IPv4 space (nearly 4 billion). The number of devices we found is almost 1.6 million, about twice as many as those using commercial search engines.","PeriodicalId":123321,"journal":{"name":"Proceedings of the 8th ACM on Multimedia Systems Conference","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121455049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Energy efficiency is a timely topic for modern mobile computing. Reducing the energy consumption of devices not only increases their battery lifetime, but also reduces the risk of hardware failure. Many researchers strive to understand the relationship between software activity and hardware power usage. A recurring strategy for saving power is to reduce operating frequencies. It is widely acknowledged that standard frequency scaling algorithms generally overreact to changes in hardware utilisation. More recent and original efforts attempt to balance software workloads on heterogeneous multicore architectures, such as the Tegra K1, which includes a quad-core CPU and a CUDA-capable GPU. However, it is not known whether it is possible to utilise these processor elements in parallel to save energy. Research into these types of systems are unfortunately often evaluated with the Performance Per Watt (PPW) metric, which is an unaccurate method because it ignores constant power usage from idle components. We show that this metric can end up increase energy usage on the Tegra K1, and give a false impression of how such systems consume energy. In reality, we show that it is much harder to save energy by balancing workloads between the heterogeneous cores of the Tegra K1, where we demonstrate only a 5% energy saving by offloading 10% DCT workload from the GPU to the CPU. Significantly more energy can be saved (up to 50 %) using the appropriate processor for different workloads.
{"title":"Load Balancing of Multimedia Workloads for Energy Efficiency on the Tegra K1 Multicore Architecture","authors":"K. Stokke, H. Stensland, C. Griwodz, P. Halvorsen","doi":"10.1145/3083187.3083195","DOIUrl":"https://doi.org/10.1145/3083187.3083195","url":null,"abstract":"Energy efficiency is a timely topic for modern mobile computing. Reducing the energy consumption of devices not only increases their battery lifetime, but also reduces the risk of hardware failure. Many researchers strive to understand the relationship between software activity and hardware power usage. A recurring strategy for saving power is to reduce operating frequencies. It is widely acknowledged that standard frequency scaling algorithms generally overreact to changes in hardware utilisation. More recent and original efforts attempt to balance software workloads on heterogeneous multicore architectures, such as the Tegra K1, which includes a quad-core CPU and a CUDA-capable GPU. However, it is not known whether it is possible to utilise these processor elements in parallel to save energy. Research into these types of systems are unfortunately often evaluated with the Performance Per Watt (PPW) metric, which is an unaccurate method because it ignores constant power usage from idle components. We show that this metric can end up increase energy usage on the Tegra K1, and give a false impression of how such systems consume energy. In reality, we show that it is much harder to save energy by balancing workloads between the heterogeneous cores of the Tegra K1, where we demonstrate only a 5% energy saving by offloading 10% DCT workload from the GPU to the CPU. Significantly more energy can be saved (up to 50 %) using the appropriate processor for different workloads.","PeriodicalId":123321,"journal":{"name":"Proceedings of the 8th ACM on Multimedia Systems Conference","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115027159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Bahirat, Chengyuan Lai, Ryan P. McMahan, B. Prabhakaran
With the increasing accessibility of the mobile head-mounted displays (HMDs), mobile virtual reality (VR) systems are finding applications in various areas. However, mobile HMDs are highly constrained with limited graphics processing units (GPUs), low processing power and onboard memory. Hence, VR developers must be cognizant of the number of polygons contained within their virtual environments to avoid rendering at low frame rates and inducing simulator sickness. The most robust and rapid approach to keeping the overall number of polygons low is to use mesh simplification algorithms to create low-poly versions of preexisting, high-poly models. Unfortunately, most existing mesh simplification algorithms cannot adequately handle meshes with lots of boundaries or non-manifold meshes, which are common attributes of 3D models made with computer-aided design tools.; AB@In this paper, we present a high-fidelity mesh simplification algorithm specifically designed for VR. This new algorithm, QEM4VR, addresses the deficiencies of prior quadric error metric (QEM) approaches by leveraging the insight that the most relevant boundary edges lie along curvatures while linear boundary edges can be collapsed. Additionally, our QEM4VR algorithm preserves key surface properties, such as normals, texture coordinates, colors, and materials. It pre-processes the 3D models and generate their low-poly approximations offline. We used six publicly available, high-poly models, with and without textures to compare the accuracy and fidelity of our QEM4VR algorithm to previous QEM variations. We also performed a frame rate analysis with original high-poly models and low-poly models obtained using QEM4VR and previous QEM variations. Our results indicate that QEM4VR creates low-poly, high-fidelity virtual environments for VR applications on devices that are constrained by the low number of polygons they can work with.
{"title":"A Boundary and Texture Preserving Mesh Simplification Algorithm for Virtual Reality","authors":"K. Bahirat, Chengyuan Lai, Ryan P. McMahan, B. Prabhakaran","doi":"10.1145/3083187.3083188","DOIUrl":"https://doi.org/10.1145/3083187.3083188","url":null,"abstract":"With the increasing accessibility of the mobile head-mounted displays (HMDs), mobile virtual reality (VR) systems are finding applications in various areas. However, mobile HMDs are highly constrained with limited graphics processing units (GPUs), low processing power and onboard memory. Hence, VR developers must be cognizant of the number of polygons contained within their virtual environments to avoid rendering at low frame rates and inducing simulator sickness. The most robust and rapid approach to keeping the overall number of polygons low is to use mesh simplification algorithms to create low-poly versions of preexisting, high-poly models. Unfortunately, most existing mesh simplification algorithms cannot adequately handle meshes with lots of boundaries or non-manifold meshes, which are common attributes of 3D models made with computer-aided design tools.; AB@In this paper, we present a high-fidelity mesh simplification algorithm specifically designed for VR. This new algorithm, QEM4VR, addresses the deficiencies of prior quadric error metric (QEM) approaches by leveraging the insight that the most relevant boundary edges lie along curvatures while linear boundary edges can be collapsed. Additionally, our QEM4VR algorithm preserves key surface properties, such as normals, texture coordinates, colors, and materials. It pre-processes the 3D models and generate their low-poly approximations offline. We used six publicly available, high-poly models, with and without textures to compare the accuracy and fidelity of our QEM4VR algorithm to previous QEM variations. We also performed a frame rate analysis with original high-poly models and low-poly models obtained using QEM4VR and previous QEM variations. Our results indicate that QEM4VR creates low-poly, high-fidelity virtual environments for VR applications on devices that are constrained by the low number of polygons they can work with.","PeriodicalId":123321,"journal":{"name":"Proceedings of the 8th ACM on Multimedia Systems Conference","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131021898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Internet of Things (IoT) is a fundamental change to the nature of the Internet whereby a massive and diverse range of objects will become network addressable. This may be the networking of previously discrete devices but also the embedding of computers into devices or components that did not previously have it. Not all connected devices have the same access needs nor rights, and network access control must be able to address the diversity effectively. Using a Software Defined Networking (SDN) approach with captive portals and port based network access (IEEE 802.1X) this paper demonstrates the first network access control (NAC) using SDN through judicious use of multiple flow tables in the widely used OpenFlow v1.3 protocol. We show that the 802.1X approach requires up to 72% fewer packets to be exchanged compared to the captive portal approach and up to 80% reduction in terms of authentication delay. Our results also show that access control via DHCP, DNS and HTTP services experience similar authentication delays because the dominant delay is due to the OpenFlow control channel delay. The work presented herein makes significant progress towards empowering network administrators with fine grained control over WiFi networks.
{"title":"WiFi Network Access Control for IoT Connectivity with Software Defined Networking","authors":"Michael Baird, Bryan K. F. Ng, Winston K.G. Seah","doi":"10.1145/3083187.3084021","DOIUrl":"https://doi.org/10.1145/3083187.3084021","url":null,"abstract":"The Internet of Things (IoT) is a fundamental change to the nature of the Internet whereby a massive and diverse range of objects will become network addressable. This may be the networking of previously discrete devices but also the embedding of computers into devices or components that did not previously have it. Not all connected devices have the same access needs nor rights, and network access control must be able to address the diversity effectively. Using a Software Defined Networking (SDN) approach with captive portals and port based network access (IEEE 802.1X) this paper demonstrates the first network access control (NAC) using SDN through judicious use of multiple flow tables in the widely used OpenFlow v1.3 protocol. We show that the 802.1X approach requires up to 72% fewer packets to be exchanged compared to the captive portal approach and up to 80% reduction in terms of authentication delay. Our results also show that access control via DHCP, DNS and HTTP services experience similar authentication delays because the dominant delay is due to the OpenFlow control channel delay. The work presented herein makes significant progress towards empowering network administrators with fine grained control over WiFi networks.","PeriodicalId":123321,"journal":{"name":"Proceedings of the 8th ACM on Multimedia Systems Conference","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126227073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gylfi Þór Guðmundsson, L. Amsaleg, B. Jónsson, M. Franklin
Computing power has now become abundant with multi-core machines, grids and clouds, but it remains a challenge to harness the available power and move towards gracefully handling web-scale datasets. Several researchers have used automatically distributed computing frameworks, notably Hadoop and Spark, for processing multimedia material, but mostly using small collections on small clusters. In this paper, we describe the engineering process for a prototype of a (near) web-scale multimedia service using the Spark framework running on the AWS cloud service. We present experimental results using up to 43 billion SIFT feature vectors from the public YFCC 100M collection, making this the largest high-dimensional feature vector collection reported in the literature. The design of the prototype and performance results demonstrate both the flexibility and scalability of the Spark framework for implementing multimedia services.
{"title":"Towards Engineering a Web-Scale Multimedia Service: A Case Study Using Spark","authors":"Gylfi Þór Guðmundsson, L. Amsaleg, B. Jónsson, M. Franklin","doi":"10.1145/3083187.3083200","DOIUrl":"https://doi.org/10.1145/3083187.3083200","url":null,"abstract":"Computing power has now become abundant with multi-core machines, grids and clouds, but it remains a challenge to harness the available power and move towards gracefully handling web-scale datasets. Several researchers have used automatically distributed computing frameworks, notably Hadoop and Spark, for processing multimedia material, but mostly using small collections on small clusters. In this paper, we describe the engineering process for a prototype of a (near) web-scale multimedia service using the Spark framework running on the AWS cloud service. We present experimental results using up to 43 billion SIFT feature vectors from the public YFCC 100M collection, making this the largest high-dimensional feature vector collection reported in the literature. The design of the prototype and performance results demonstrate both the flexibility and scalability of the Spark framework for implementing multimedia services.","PeriodicalId":123321,"journal":{"name":"Proceedings of the 8th ACM on Multimedia Systems Conference","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116129828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
360 degree video is anew generation of video streaming technology that promises greater immersiveness than standard video streams. This level of immersiveness is similar to that produced by virtual reality devices -- users can control the field of view using head movements rather than needing to manipulate external devices. Although 360 degree video could revolutionize streaming technology, large scale adoption is hindered by a number of factors. 360 degree video streams have larger bandwidth requirements, require faster responsiveness to user inputs, and users may be more sensitive to lower quality streams.; AB@In this paper, we review standard approaches toward 360 degree video encoding and compare these to a new, as yet unpublished, approach by Oculus which we refer to as the offset cubic projection. Compared to the standard cubic encoding, the offset cube encodes a distorted version of the spherical surface, devoting more information (i.e., pixels) to the view in a chosen direction. We estimate that the offset cube representation can produce better or similar visual quality while using less than 50% pixels under reasonable assumptions about user behavior, resulting in 5.6% to 16.4% average savings in video bitrate. During 360 degree video streaming, Oculus uses a combination of quality level adaptation and view orientation adaptation. We estimate that this combination of streaming adaptation in two dimensions can cause over 57% extra segments to be downloaded compared to an ideal downloading strategy, wasting 20% of the total downloading bandwidth.
{"title":"A Measurement Study of Oculus 360 Degree Video Streaming","authors":"Chao Zhou, Zhenhua Li, Yao Liu","doi":"10.1145/3083187.3083190","DOIUrl":"https://doi.org/10.1145/3083187.3083190","url":null,"abstract":"360 degree video is anew generation of video streaming technology that promises greater immersiveness than standard video streams. This level of immersiveness is similar to that produced by virtual reality devices -- users can control the field of view using head movements rather than needing to manipulate external devices. Although 360 degree video could revolutionize streaming technology, large scale adoption is hindered by a number of factors. 360 degree video streams have larger bandwidth requirements, require faster responsiveness to user inputs, and users may be more sensitive to lower quality streams.; AB@In this paper, we review standard approaches toward 360 degree video encoding and compare these to a new, as yet unpublished, approach by Oculus which we refer to as the offset cubic projection. Compared to the standard cubic encoding, the offset cube encodes a distorted version of the spherical surface, devoting more information (i.e., pixels) to the view in a chosen direction. We estimate that the offset cube representation can produce better or similar visual quality while using less than 50% pixels under reasonable assumptions about user behavior, resulting in 5.6% to 16.4% average savings in video bitrate. During 360 degree video streaming, Oculus uses a combination of quality level adaptation and view orientation adaptation. We estimate that this combination of streaming adaptation in two dimensions can cause over 57% extra segments to be downloaded compared to an ideal downloading strategy, wasting 20% of the total downloading bandwidth.","PeriodicalId":123321,"journal":{"name":"Proceedings of the 8th ACM on Multimedia Systems Conference","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126504104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Longhao Zou, Irina Tal, A. Covaci, Eva Ibarrola, G. Ghinea, Gabriel-Miro Muntean
In recent years, the emerging immersive technologies (e.g. Virtual/Augmented Reality, multisensorial media) bring brand-new multi-dimensional effects such as 3D vision, immersion, vibration, smell, airflow, etc. to gaming, video entertainment and other aspects of human life. This paper reports results from an European Horizon 2020 research project on the impact of multisensoral media (mulsemedia) on educational learner experience. A mulsemedia-enhanced test-bed was developed to perform delivery of video content enhanced with haptic, olfaction and airflow effects. The results of the quality rating and questionnaires show significant improvements in terms of mulsemedia-enhanced teaching.
{"title":"Can Multisensorial Media Improve Learner Experience?","authors":"Longhao Zou, Irina Tal, A. Covaci, Eva Ibarrola, G. Ghinea, Gabriel-Miro Muntean","doi":"10.1145/3083187.3084014","DOIUrl":"https://doi.org/10.1145/3083187.3084014","url":null,"abstract":"In recent years, the emerging immersive technologies (e.g. Virtual/Augmented Reality, multisensorial media) bring brand-new multi-dimensional effects such as 3D vision, immersion, vibration, smell, airflow, etc. to gaming, video entertainment and other aspects of human life. This paper reports results from an European Horizon 2020 research project on the impact of multisensoral media (mulsemedia) on educational learner experience. A mulsemedia-enhanced test-bed was developed to perform delivery of video content enhanced with haptic, olfaction and airflow effects. The results of the quality rating and questionnaires show significant improvements in terms of mulsemedia-enhanced teaching.","PeriodicalId":123321,"journal":{"name":"Proceedings of the 8th ACM on Multimedia Systems Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129075229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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