IEEE Journal of Selected Topics in Signal Processing

You are here

Top Reasons to Join SPS Today!

1. IEEE Signal Processing Magazine
2. Signal Processing Digital Library*
3. Inside Signal Processing Newsletter
4. SPS Resource Center
5. Career advancement & recognition
6. Discounts on conferences and publications
7. Professional networking
8. Communities for students, young professionals, and women
9. Volunteer opportunities
10. Coming soon! PDH/CEU credits
Click here to learn more.

Panoramic videos are becoming more and more easily obtained for common users. Although these videos have 360 field of view, they are usually displayed with perspective views, which needs the saliency informations for viewing angle selection. In this paper, we propose a saliency prediction network for 360 videos. Our network takes video frames and optical flows in cube map format as input, thus it does not suffer from image distorations of panoramic frames. 

Panoramic videos are becoming more and more easily obtained for common users. Although these videos have 360 field of view, they are usually displayed with perspective views, which needs the saliency informations for viewing angle selection. In this paper, we propose a saliency prediction network for 360 videos. Our network takes video frames and optical flows in cube map format as input, thus it does not suffer from image distorations of panoramic frames. 

Nowadays, 360° video/image has been increasingly popular and drawn great attention. The spherical viewing range of 360° video/image accounts for huge data, which pose the challenges to 360° video/image processing in solving the bottleneck of storage, transmission, etc. Accordingly, the recent years have witnessed the explosive emergence of works on 360° video/image processing.

Recent years have witnessed the rapid development of virtual reality (VR). Above 90% of VR content is in the form of 360° video, also called omnidirectional video or panoramic video. Generally speaking, 360° video offers immersive and interactive viewing experience, as the viewers are able to freely move their heads in the range of 360° × 180° to access different viewports.

This paper proposes nonorthogonal sharing of available resources between latency-critical and latency-tolerant communication for fulfilling tight requirements of ultrareliable low-latency communication (URLLC) as well as avoiding inefficient spectrum utilization of grant-based (GB) access for sporadic URLLC traffic.

For the Internet of Things (IoT), there might be a large number of devices to be connected to the Internet through wireless technologies. In general, IoT devices would have various constraints due to limited processing capability, memory, energy source, and so on, and it is desirable to employ efficient wireless transmission schemes, especially for uplink transmissions.

The last few years have witnessed a tremendous growth of the demand for wireless services and a significant increase of the number of mobile subscribers. A recent data traffic forecast from Cisco reported that the global mobile data traffic reached 1.2 zettabytes per year in 2016, and the global IP traffic will increase nearly threefold over the next 5 years.

A novel scheme called dual-polarized spatial media-based modulation (DP-SMBM), which combines judiciously the media-based modulation (MBM), spatial modulation (SM), and dual-polarized (DP) antennas, is proposed in this paper. The DP-SMBM introduces a new DP domain to convey additional information without occupying extra physical space, effectively enhancing the transmission rate and alleviating the finite space issue.

Pages

SPS on Twitter

SPS Videos


Signal Processing in Home Assistants

 


Multimedia Forensics


Careers in Signal Processing             

 


Under the Radar