Error Resilient Coding Techniques for Video Delivery over Vehicular Networks

Abstract

Nowadays, more and more vehicles are equipped with communication capabilities, not only providing connectivity with onboard devices, but also with off-board communication infrastructures. From road safety (i.e., multimedia e-call) to infotainment (i.e., video on demand services), there are a lot of applications and services that may be deployed in vehicular networks, where video streaming is the key factor. As it is well known, these networks suffer from high interference levels and low available network resources, and it is a great challenge to deploy video delivery applications which provide good quality video services. We focus our work on supplying error resilience capabilities to video streams in order to fight against the high packet loss rates found in vehicular networks. So, we propose the combination of source coding and channel coding techniques. The former ones are applied in the video encoding process by means of intra-refresh coding modes and tile-based frame partitioning techniques. The latter one is based on the use of forward error correction mechanisms in order to recover as many lost packets as possible. We have carried out an extensive evaluation process to measure the error resilience capabilities of both approaches in both (a) a simple packet error probabilistic model, and (b) a realistic vehicular network simulation framework. Results show that forward error correction mechanisms are mandatory to guarantee video delivery with an acceptable quality level , and we highly recommend the use of the proposed mechanisms to increase even more the final video quality.

Adaptive radio propagation model for maximizing performance efficiency in smart city disaster management application

“…In addition, it is essential to note that the signal being transmitted could become distorted due to the blocking consequences associated with the fresnel-zone ellipsoid (FZE) caused by MNs. These effects can be approximated utilizing the given as (13).…”

“…𝑟 𝑎𝑓𝑓 𝑟 + 𝑧 𝑥 − 0.6𝑠 𝑘 + 𝑧 𝑡 (13) Where, 𝑟 𝑎𝑓𝑓 is used for representing the distance among the MNs which are obstructing and transmitting, 𝑧 𝑥 and 𝑧 𝑦 are used for representing the height parameter of the MNs 𝑥 transmitter and MNs 𝑦 receiver respectively, 𝑧 𝑡 is used for representing the height of the antenna of the MNs, 𝑟 is used for representing the distance among the transmitting MNs and receiving MNs and 𝑠 𝑘 is used for representing the FZE value which is obtained using the given as (14).…”

“…These challenges can hinder reliable and timely video transmission, impacting communication and coordination efforts during disasters. Addressing these challenges requires innovative solutions such as adaptive transmission technique [11], optimized network infrastructure deployment [12], robust error correction mechanism [13], and efficient bandwidth management algorithm [14]. Overcoming these challenges is crucial to ensure effective video transmission that supports situational awareness, decision-making, and coordination in urban disaster management operations.…”

Video Error-Resilience Research Based on Error-Resilient Screen Content

“…Different from classical error-resilient coding algorithms, such as [20][21][22][23], the proposed scheme in this paper provides an adaptive error prevention coding mechanism for frame level-based video transmission security. The total end-to-end rate-distortion cost can be optimized by adjusting the number of coded redundant frames.…”

Gradual Saliency Detection in Video Sequences Using Bottom-up Attributes

“…The base layer can provide a low but acceptable level of quality, and enhancement layers incrementally improve the streaming video quality. This coding technique is also called scalable coding [6,7]. The gradual saliency technique can provide guidance for the encoder to dynamically decide what regions of video data are more salient and must form the base layer.…”