Advances in wireless technology will soon provide sufficient capacity for the transmission of compressed video to and from mobile terminals. However, high compression ratios and the use of Variable Length Coding in standards such as H.263 and MPEG-4 make the encoded bitstreams particularly sensitive to errors. This thesis investigates methods for the error robust transmission of MPEG-4 coded video over mobile networks. It examines curent and future mobile networks, and discusses the quality of service that they are expected to offer with respect to mobile multimedia. Also, the MPEG-4 systems and visual layer standards are briefly described. Real-time MPEG-4 encoder and decoder software has been developed and exploited in the work described here. The MPEG-4 software can send MPEG-4 data over TCP or over RTP. All of the standard MPEG•4 error resilience options are implemented in the software. The effectiveness of these options is demonstrated through the results of simulated transmission over a GPRS channel. MPEG•4 is separated into two different streams via exploitation of the data partitioning option. The two streams may then be transmitted over a mobile network using different bearer channels. The most sensitive data stream is sent using a bearer channel with a low bit error rate compared to the less sensitive data stream. This technique is shown to produce quality improvements. A technique for the insertion of user-defined data is outlined. Insertion of user- defined data is achieved while retaining backwards compatibility with existing standard MPEG- 4 decoders. CRC codes are inserted using this scheme, to facilitate more accurate detection of errors. This error detection aids error concealment and results in a gain in decoded video quality after simulated transmission over a GPRS channel. Motion adaptive encoding is employed to increase the error robustness of the encoded bitstream. Video packet size and Intra block refresh rates are altered with first partition size, which is used as a guide to the amount of motion within a scene. 1Tansmlssion of video using RTP is considered. In particular, a mathematical analysis is performed for two different packetisation schemes. One scheme encapsulates one video frame within one RTP packet, while the other scheme encapsulates a single video packet within a single RTP packet.

International Telemetering Conference Proceedings / October 23-26, 2000 / Town & Country Hotel and Conference Center, San Diego, California / Compressed video is necessary for a variety of telemetry requirements. A large number of competing video compression algorithms exist. This paper compares the ability of these algorithms to meet criteria which are of interest for telemetry applications. Included are: quality, compression, noise susceptibility, motion performance and latency. The algorithms are divided into those which employ inter-frame compression and those which employ intra-frame compression. A video tape presentation will also be presented to illustrate the performance of the video compression algorithms.

Automatic tracking and video of surveillance on a farm could help to support farm management. In this project, an automated detection system is used to detect sows in surveillance videos. This system is based upon deep learning and computer vision methods. In order to minimize disk storage and to meet the network requirements necessary to achieve the real-performance, tracking in compressed video streams is essential. The proposed system uses a Discriminative Correlation Filter (DCF) as a classifier to detect targets. The tracking model is updated by training the classifier with online learning methods. Compression technology encodes the video data, thus reducing both the bit rates at which video signals are transmitted and helping the video transmission better adapt to the limited network bandwidth. However, compression may reduce the image quality of the videos the precision of our tracking may decrease. Hence, we conducted a performance evaluation of existing visual tracking algorithms on video sequences with quality degradation due to various compression parameters (encoders, target bitrate, rate control model, and Group of Pictures (GOP) size). The ultimate goal of video compression is to realize a tracking system with equal performance, but requiring fewer network resources. The proposed tracking algorithm successfully tracks each sow in consecutive frames in most cases. The performance of our tracker was benchmarked against two state-of-art tracking algorithms: Siamese Fully-Convolutional (FC) and Efficient Convolution Operators (ECO). The performance evaluation result shows our proposed tracker has similar performance to both Siamese FC and ECO. In comparison with the original tracker, the proposed tracker achieved similar tracking performance, while requiring much less storage and generating a lower bitrate when the video was compressed with appropriate parameters. However, the system is far slower than needed for real-time tracking due to high computational complexity; therefore, more optimal methods to update the tracking model will be needed to achieve real-time tracking. / Automatisk spårning av övervakning i gårdens område kan bidra till att stödja jordbruket management. I detta projekt till ett automatiserat system för upptäckt upptäcka suggor från övervaknings filmer kommer att utformas med djupa lärande och datorseende metoder. Av hänsyn till Diskhantering och tid och hastighet Krav över nätverket för att uppnå realtidsscenarier i framtiden är spårning i komprimerade videoströmmar är avgörande. Det föreslagna systemet i detta projekt skulle använda en DCF (diskriminerande korrelationsfilter) som en klassificerare att upptäcka mål. Spårningen modell kommer att uppdateras genom att utbilda klassificeraren med online inlärningsmetoder. Compression teknik kodar videodata och minskar bithastigheter där videosignaler sänds kan hjälpa videoöverföring anpassar bättre i begränsad nätverk. det kan dock reducera bildkvaliteten på videoklipp och leder exakt hastighet av vårt spårningssystem för att minska. Därför undersöker vi utvärderingen av prestanda av befintlig visuella spårningsalgoritmer på videosekvenser Det ultimata målet med videokomprimering är att bidra till att bygga ett spårningssystem med samma prestanda men kräver färre nätverksresurser. Den föreslagna spårning algoritm spår framgångsrikt varje sugga i konsekutiva ramar i de flesta fall prestanda vår tracker var jämföras med två state-of-art spårning algoritmer:. Siamese Fully-Convolutional (FC) och Efficient Convolution Operators (ECO) utvärdering av prestanda Resultatet visar vår föreslagna tracker blir liknande prestanda med Siamese FC och ECO. I jämförelse med den ursprungliga spårningen uppnådde den föreslagna spårningen liknande spårningseffektivitet, samtidigt som det krävde mycket mindre lagring och alstra en lägre bitrate när videon komprimerades med lämpliga parametrar. Systemet är mycket långsammare än det behövs för spårning i realtid på grund av hög beräkningskomplexitet; därför behövs mer optimala metoder för att uppdatera spårningsmodellen för att uppnå realtidsspårning.