Detection of video double encoding with GOP size estimation

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Semi-hierarchical based motion estimation algorithm for the dirac video encoder

Having fast and efficient motion estimation is crucial in today’s advance video compression technique since it determines the compression efficiency and the complexity of a video encoder. In this paper, a method which we call semi-hierarchical motion estimation is proposed for the Dirac video encoder. By considering the fully hierarchical motion estimation only for a certain type of inter frame encoding, complexity of the motion estimation can be greatly reduced while maintaining the desirable accuracy. The experimental results show that the proposed algorithm gives two to three times reduction in terms of the number of SAD calculation compared with existing motion estimation algorithm of Dirac for the same motion estimation accuracy, compression efficiency and PSNR performance. Moreover, depending upon the complexity of the test sequence, the proposed algorithm has the ability to increase or decrease the search range in order to maintain the accuracy of the motion estimation to a certain level

Surveillance centric coding

PhDThe research work presented in this thesis focuses on the development of techniques specific to surveillance videos for efficient video compression with higher processing speed. The Scalable Video Coding (SVC) techniques are explored to achieve higher compression efficiency. The framework of SVC is modified to support Surveillance Centric Coding (SCC). Motion estimation techniques specific to surveillance videos are proposed in order to speed up the compression process of the SCC. The main contributions of the research work presented in this thesis are divided into two groups (i) Efficient Compression and (ii) Efficient Motion Estimation. The paradigm of Surveillance Centric Coding (SCC) is introduced, in which coding aims to achieve bit-rate optimisation and adaptation of surveillance videos for storing and transmission purposes. In the proposed approach the SCC encoder communicates with the Video Content Analysis (VCA) module that detects events of interest in video captured by the CCTV. Bit-rate optimisation and adaptation are achieved by exploiting the scalability properties of the employed codec. Time segments containing events relevant to surveillance application are encoded using high spatiotemporal resolution and quality while the irrelevant portions from the surveillance standpoint are encoded at low spatio-temporal resolution and / or quality. Thanks to the scalability of the resulting compressed bit-stream, additional bit-rate adaptation is possible; for instance for the transmission purposes. Experimental evaluation showed that significant reduction in bit-rate can be achieved by the proposed approach without loss of information relevant to surveillance applications. In addition to more optimal compression strategy, novel approaches to performing efficient motion estimation specific to surveillance videos are proposed and implemented with experimental results. A real-time background subtractor is used to detect the presence of any motion activity in the sequence. Different approaches for selective motion estimation, GOP based, Frame based and Block based, are implemented. In the former, motion estimation is performed for the whole group of pictures (GOP) only when a moving object is detected for any frame of the GOP. iii While for the Frame based approach; each frame is tested for the motion activity and consequently for selective motion estimation. The selective motion estimation approach is further explored at a lower level as Block based selective motion estimation. Experimental evaluation showed that significant reduction in computational complexity can be achieved by applying the proposed strategy. In addition to selective motion estimation, a tracker based motion estimation and fast full search using multiple reference frames has been proposed for the surveillance videos. Extensive testing on different surveillance videos shows benefits of application of proposed approaches to achieve the goals of the SCC

H4VDM: H.264 Video Device Matching

Methods that can determine if two given video sequences are captured by the same device (e.g., mobile telephone or digital camera) can be used in many forensics tasks. In this paper we refer to this as "video device matching". In open-set video forensics scenarios it is easier to determine if two video sequences were captured with the same device than identifying the specific device. In this paper, we propose a technique for open-set video device matching. Given two H.264 compressed video sequences, our method can determine if they are captured by the same device, even if our method has never encountered the device in training. We denote our proposed technique as H.264 Video Device Matching (H4VDM). H4VDM uses H.264 compression information extracted from video sequences to make decisions. It is more robust against artifacts that alter camera sensor fingerprints, and it can be used to analyze relatively small fragments of the H.264 sequence. We trained and tested our method on a publicly available video forensics dataset consisting of 35 devices, where our proposed method demonstrated good performance

Video Inter-frame Forgery Detection Approach for Surveillance and Mobile Recorded Videos

We are living in an age where use of multimedia technologies like digital recorders and mobile phones is increasing rapidly. On the other hand, digital content manipulating softwares are also increasing making it easy for an individual to doctor the recorded content with trivial consumption of time and wealth. Digital multimedia forensics is gaining utmost importance to restrict unethical use of such easily available tampering techniques. These days, it is common for people to record videos using their smart phones. We have also witnessed a sudden growth in the use of surveillance cameras, which we see inhabiting almost every public location. Videos recorded using these devices usually contains crucial evidence of some event occurence and thereby most susceptible to inter-frame forgery which can be easily performed by insertion/removal/replication of frame(s). The proposed forensic technique enabled detection of inter-frame forgery in H.264 and MPEG-2 encoded videos especially mobile recorded and surveillance videos. This novel method introduced objectivity for automatic detection and localization of tampering by utilizing prediction residual gradient and optical flow gradient. Experimental results showed that this technique can detect tampering with 90% true positive rate, regardless of the video codec and recording device utilized and number of frames tampered

Semi-hierarchical based motion estimation algorithm for the dirac video encoder

Having fast and efficient motion estimation is crucial in today’s advance video compression technique since it determines the compression efficiency and the complexity of a video encoder. In this paper, a method which we call semi-hierarchical motion estimation is proposed for the Dirac video encoder. By considering the fully hierarchical motion estimation only for a certain type of inter frame encoding, complexity of the motion estimation can be greatly reduced while maintaining the desirable accuracy. The experimental results show that the proposed algorithm gives two to three times reduction in terms of the number of SAD calculation compared with existing motion estimation algorithm of Dirac for the same motion estimation accuracy, compression efficiency and PSNR performance. Moreover, depending upon the complexity of the test sequence, the proposed algorithm has the ability to increase or decrease the search range in order to maintain the accuracy of the motion estimation to a certain level