Identifying inter-frame forgery is a hot topic in video forensics. In this paper, we propose a method based on the assumption that the correlation coefficients of gray values is consistent in an original video, while ...Identifying inter-frame forgery is a hot topic in video forensics. In this paper, we propose a method based on the assumption that the correlation coefficients of gray values is consistent in an original video, while in forgeries the consistency will be destroyed. We first extract the consistency of correlation coefficients of gray values (CCCoGV for short) after normalization and quantization as distinguishing feature to identify interframe forgeries. Then we test the CCCoGV in a large database with the help of SVM (Support Vector Machine). Experimental results show that the proposed method is efficient in classifying original videos and forgeries. Furthermore, the proposed method performs also pretty well in classifying frame insertion and frame deletion forgeries.展开更多
Video surveillance system is used in various fields such as transportation and social life.The bad weather can lead to the degradation of the video surveillance image quality.In rainy environment,the raindrops and the...Video surveillance system is used in various fields such as transportation and social life.The bad weather can lead to the degradation of the video surveillance image quality.In rainy environment,the raindrops and the background are mixed,which lead to make the image degradation,so the removal of the raindrops has great significance for image restoration.In this article,after analyzing the inter-frame difference method in detecting and removing raindrops,a background difference method is proposed based on Gaussian model.In this method,the raindrop is regarded as a moving object relative to the background.The principle and procedure of the method are given to detect and remove raindrops.The parameters of the single Gaussian background model are studied in this article.The important parameter of the learning rate of Gaussian model is explored in order to better detection and removal of raindrops.Experiment shows that the results of removal of raindrops by using the proposed algorithm are better than that by using the inter-frame difference method.The image processing effect is the best when the learning rate is 0.6.The research results can provide technical reference for similar research on eliminating the influence of rainy weather.展开更多
This paper presents an effective machine learning-based depth selection algorithm for CTU(Coding Tree Unit)in HEVC(High Efficiency Video Coding).Existing machine learning methods are limited in their ability in handli...This paper presents an effective machine learning-based depth selection algorithm for CTU(Coding Tree Unit)in HEVC(High Efficiency Video Coding).Existing machine learning methods are limited in their ability in handling the initial depth decision of CU(Coding Unit)and selecting the proper set of input features for the depth selection model.In this paper,we first propose a new classification approach for the initial division depth prediction.In particular,we study the correlation of the texture complexity,QPs(quantization parameters)and the depth decision of the CUs to forecast the original partition depth of the current CUs.Secondly,we further aim to determine the input features of the classifier by analysing the correlation between depth decision of the CUs,picture distortion and the bit-rate.Using the found relationships,we also study a decision method for the end partition depth of the current CUs using bit-rate and picture distortion as input.Finally,we formulate the depth division of the CUs as a binary classification problem and use the nearest neighbor classifier to conduct classification.Our proposed method can significantly improve the efficiency of interframe coding by circumventing the traversing cost of the division depth.It shows that the mentioned method can reduce the time spent by 34.56%compared to HM-16.9 while keeping the partition depth of the CUs correct.展开更多
Video shreds of evidence are usually admissible in the court of law all over the world. However, individuals manipulate these videos to either defame or incriminate innocent people. Others indulge in video tampering t...Video shreds of evidence are usually admissible in the court of law all over the world. However, individuals manipulate these videos to either defame or incriminate innocent people. Others indulge in video tampering to falsely escape the wrath of the law against misconducts. One way impostors can forge these videos is through inter-frame video forgery. Thus, the integrity of such videos is under threat. This is because these digital forgeries seriously debase the credibility of video contents as being definite records of events. <span style="font-family:Verdana;">This leads to an increasing concern about the trustworthiness of video contents. Hence, it continues to affect the social and legal system, forensic investigations, intelligence services, and security and surveillance systems as the case may be. The problem of inter-frame video forgery is increasingly spontaneous as more video-editing software continues to emerge. These video editing tools can easily manipulate videos without leaving obvious traces and these tampered videos become viral. Alarmingly, even the beginner users of these editing tools can alter the contents of digital videos in a manner that renders them practically indistinguishable from the original content by mere observations. </span><span style="font-family:Verdana;">This paper, however, leveraged on the concept of correlation coefficients to produce a more elaborate and reliable inter-frame video detection to aid forensic investigations, especially in Nigeria. The model employed the use of the idea of a threshold to efficiently distinguish forged videos from authentic videos. A benchmark and locally manipulated video datasets were used to evaluate the proposed model. Experimentally, our approach performed better than the existing methods. The overall accuracy for all the evaluation metrics such as accuracy, recall, precision and F1-score was 100%. The proposed method implemented in the MATLAB programming language has proven to effectively detect inter-frame forgeries.</span>展开更多
Error-resilient video communication over lossy packet networks is often designed and operated based on models for the effect of losses on the reconstructed video quality. This paper analyzes the channel distortion for...Error-resilient video communication over lossy packet networks is often designed and operated based on models for the effect of losses on the reconstructed video quality. This paper analyzes the channel distortion for video over lossy packet networks and proposes a new model that, compared to previous models, more accurately estimates the expected mean-squared error distortion for different packet loss patterns by accounting for inter-frame error propagation and the correlation between error frames. The accuracy of the proposed model is validated with JVT/H.264 encoded standard test sequences and previous frame concealment, where the proposed model provides an obvious accuracy gain over previous models.展开更多
To compress screen image sequence in real-time remote and interactive applications,a novel compression method is proposed.The proposed method is named as CABHG.CABHG employs hybrid coding schemes that consist of intra...To compress screen image sequence in real-time remote and interactive applications,a novel compression method is proposed.The proposed method is named as CABHG.CABHG employs hybrid coding schemes that consist of intra-frame and inter-frame coding modes.The intra-frame coding is a rate-distortion optimized adaptive block size that can be also used for the compression of a single screen image.The inter-frame coding utilizes hierarchical group of pictures(GOP) structure to improve system performance during random accesses and fast-backward scans.Experimental results demonstrate that the proposed CABHG method has approximately 47%-48% higher compression ratio and 46%-53% lower CPU utilization than professional screen image sequence codecs such as TechSmith Ensharpen codec and Sorenson 3 codec.Compared with general video codecs such as H.264 codec,XviD MPEG-4 codec and Apple's Animation codec,CABHG also shows 87%-88% higher compression ratio and 64%-81% lower CPU utilization than these general video codecs.展开更多
Visual navigation is imperative for successful asteroid exploration missions.In this study,an integrated visual navigation system was proposed based on angles-only measurements to robustly and accurately determine the...Visual navigation is imperative for successful asteroid exploration missions.In this study,an integrated visual navigation system was proposed based on angles-only measurements to robustly and accurately determine the pose of the lander during the final landing phase.The system used the lander's global pose information provided by an orbiter,which was deployed in space in advance,and its relative motion information in adjacent images to jointly estimate its optimal state.First,the landmarks on the asteroid surface and markers on the lander were identified from the images acquired by the orbiter.Subsequently,an angles-only measurement model concerning the landmarks and markers was constructed to estimate the orbiter's position and lander's pose.Subsequently,a method based on the epipolar constraint was proposed to estimate the lander's inter-frame motion.Then,the absolute pose and relative motion of the lander were fused using an extended Kalman filter.Additionally,the observability criterion and covariance of the state error were provided.Finally,synthetic image sequences were generated to validate the proposed navigation system,and numerical results demonstrated its advance in terms of robustness and accuracy.展开更多
Plantar Region of Interest （ROI） detection is important for the early diagnosis and treatment ofmorphologic defects of the foot and foot bionic research. Conventional methods have employed complex procedures and exp...Plantar Region of Interest （ROI） detection is important for the early diagnosis and treatment ofmorphologic defects of the foot and foot bionic research. Conventional methods have employed complex procedures and expensive instruments which prohibit their widespread use in healthcare. In this paper an automatic plantar ROIs detection method using a customized low-cost pressure acquisition device is proposed. Plantar pressure data and 3D motion capture data were collected from 28 subjects （14 healthy subjects and 14 subjects with hallux valgus）. The maximal inter-frame difference during the stance phase was calculated. Consequently, the ROIs were defined by the first-order difference in combination with prior anatomic knowl- edge. The anatomic locations were determined by the maximal inter-frame difference and second maximal inter-frame differ- ence, which nearly coincided. Our system can achieve average recognition accuracies of 92.90%, 89.30%, 89.30%, 92.90%, 92.90%, and 89.30% for plantar ROIs hallux and metatarsi I-V, respectively, as compared with the annotations using the 3D motion capture system. The maximal difference of metatarsus heads II-V, and the impulse of the medial and lateral heel features made a significant contribution to the classification ofhallux valgus and healthy subjects with ≥ 80% sensitivity and specificity. Furthermore, the plantar pressure acquisition system is portable and convenient to use, thus can be used in home- or commu- nity-based healthcare applications.展开更多
文摘Identifying inter-frame forgery is a hot topic in video forensics. In this paper, we propose a method based on the assumption that the correlation coefficients of gray values is consistent in an original video, while in forgeries the consistency will be destroyed. We first extract the consistency of correlation coefficients of gray values (CCCoGV for short) after normalization and quantization as distinguishing feature to identify interframe forgeries. Then we test the CCCoGV in a large database with the help of SVM (Support Vector Machine). Experimental results show that the proposed method is efficient in classifying original videos and forgeries. Furthermore, the proposed method performs also pretty well in classifying frame insertion and frame deletion forgeries.
基金This work was supported by Henan Province Science and Technology Project under Grant No.182102210065.
文摘Video surveillance system is used in various fields such as transportation and social life.The bad weather can lead to the degradation of the video surveillance image quality.In rainy environment,the raindrops and the background are mixed,which lead to make the image degradation,so the removal of the raindrops has great significance for image restoration.In this article,after analyzing the inter-frame difference method in detecting and removing raindrops,a background difference method is proposed based on Gaussian model.In this method,the raindrop is regarded as a moving object relative to the background.The principle and procedure of the method are given to detect and remove raindrops.The parameters of the single Gaussian background model are studied in this article.The important parameter of the learning rate of Gaussian model is explored in order to better detection and removal of raindrops.Experiment shows that the results of removal of raindrops by using the proposed algorithm are better than that by using the inter-frame difference method.The image processing effect is the best when the learning rate is 0.6.The research results can provide technical reference for similar research on eliminating the influence of rainy weather.
基金This paper is supported by the National Natural Science Foundation of China(61672064)Basic Research Program of Qinghai Province(No.2020-ZJ-709)the project for advanced information network Beijing laboratory(PXM2019_014204_500029).
文摘This paper presents an effective machine learning-based depth selection algorithm for CTU(Coding Tree Unit)in HEVC(High Efficiency Video Coding).Existing machine learning methods are limited in their ability in handling the initial depth decision of CU(Coding Unit)and selecting the proper set of input features for the depth selection model.In this paper,we first propose a new classification approach for the initial division depth prediction.In particular,we study the correlation of the texture complexity,QPs(quantization parameters)and the depth decision of the CUs to forecast the original partition depth of the current CUs.Secondly,we further aim to determine the input features of the classifier by analysing the correlation between depth decision of the CUs,picture distortion and the bit-rate.Using the found relationships,we also study a decision method for the end partition depth of the current CUs using bit-rate and picture distortion as input.Finally,we formulate the depth division of the CUs as a binary classification problem and use the nearest neighbor classifier to conduct classification.Our proposed method can significantly improve the efficiency of interframe coding by circumventing the traversing cost of the division depth.It shows that the mentioned method can reduce the time spent by 34.56%compared to HM-16.9 while keeping the partition depth of the CUs correct.
文摘Video shreds of evidence are usually admissible in the court of law all over the world. However, individuals manipulate these videos to either defame or incriminate innocent people. Others indulge in video tampering to falsely escape the wrath of the law against misconducts. One way impostors can forge these videos is through inter-frame video forgery. Thus, the integrity of such videos is under threat. This is because these digital forgeries seriously debase the credibility of video contents as being definite records of events. <span style="font-family:Verdana;">This leads to an increasing concern about the trustworthiness of video contents. Hence, it continues to affect the social and legal system, forensic investigations, intelligence services, and security and surveillance systems as the case may be. The problem of inter-frame video forgery is increasingly spontaneous as more video-editing software continues to emerge. These video editing tools can easily manipulate videos without leaving obvious traces and these tampered videos become viral. Alarmingly, even the beginner users of these editing tools can alter the contents of digital videos in a manner that renders them practically indistinguishable from the original content by mere observations. </span><span style="font-family:Verdana;">This paper, however, leveraged on the concept of correlation coefficients to produce a more elaborate and reliable inter-frame video detection to aid forensic investigations, especially in Nigeria. The model employed the use of the idea of a threshold to efficiently distinguish forged videos from authentic videos. A benchmark and locally manipulated video datasets were used to evaluate the proposed model. Experimentally, our approach performed better than the existing methods. The overall accuracy for all the evaluation metrics such as accuracy, recall, precision and F1-score was 100%. The proposed method implemented in the MATLAB programming language has proven to effectively detect inter-frame forgeries.</span>
基金Project (No. Y2001005) supported by the Natural Science Foundation of Shandong Province, China
文摘Error-resilient video communication over lossy packet networks is often designed and operated based on models for the effect of losses on the reconstructed video quality. This paper analyzes the channel distortion for video over lossy packet networks and proposes a new model that, compared to previous models, more accurately estimates the expected mean-squared error distortion for different packet loss patterns by accounting for inter-frame error propagation and the correlation between error frames. The accuracy of the proposed model is validated with JVT/H.264 encoded standard test sequences and previous frame concealment, where the proposed model provides an obvious accuracy gain over previous models.
基金Project(60873230) supported by the National Natural Science Foundation of China
文摘To compress screen image sequence in real-time remote and interactive applications,a novel compression method is proposed.The proposed method is named as CABHG.CABHG employs hybrid coding schemes that consist of intra-frame and inter-frame coding modes.The intra-frame coding is a rate-distortion optimized adaptive block size that can be also used for the compression of a single screen image.The inter-frame coding utilizes hierarchical group of pictures(GOP) structure to improve system performance during random accesses and fast-backward scans.Experimental results demonstrate that the proposed CABHG method has approximately 47%-48% higher compression ratio and 46%-53% lower CPU utilization than professional screen image sequence codecs such as TechSmith Ensharpen codec and Sorenson 3 codec.Compared with general video codecs such as H.264 codec,XviD MPEG-4 codec and Apple's Animation codec,CABHG also shows 87%-88% higher compression ratio and 64%-81% lower CPU utilization than these general video codecs.
基金supported by the National Natural Science Foundation of China(Grant Nos.61673057 and 61803028)。
文摘Visual navigation is imperative for successful asteroid exploration missions.In this study,an integrated visual navigation system was proposed based on angles-only measurements to robustly and accurately determine the pose of the lander during the final landing phase.The system used the lander's global pose information provided by an orbiter,which was deployed in space in advance,and its relative motion information in adjacent images to jointly estimate its optimal state.First,the landmarks on the asteroid surface and markers on the lander were identified from the images acquired by the orbiter.Subsequently,an angles-only measurement model concerning the landmarks and markers was constructed to estimate the orbiter's position and lander's pose.Subsequently,a method based on the epipolar constraint was proposed to estimate the lander's inter-frame motion.Then,the absolute pose and relative motion of the lander were fused using an extended Kalman filter.Additionally,the observability criterion and covariance of the state error were provided.Finally,synthetic image sequences were generated to validate the proposed navigation system,and numerical results demonstrated its advance in terms of robustness and accuracy.
基金Acknowledgments This study was financed, in part, by the National Natural Science Foundation of China （Grant Nos. 60932001, 61072031, and 51105359）, the National Ba- sic Research （973） Program of China （Sub-grant 6 of Grant No. 2010CB732606）, and the Knowledge Inno- vation Program of the Chinese Academy of Sciences, and was also supported by the Guangdong Innovation Research Team Fund for Low-cost Healthcare Tech- nologies and the China Postdoctoral Science Foundation （Grant No. 2011M500402）.
文摘Plantar Region of Interest （ROI） detection is important for the early diagnosis and treatment ofmorphologic defects of the foot and foot bionic research. Conventional methods have employed complex procedures and expensive instruments which prohibit their widespread use in healthcare. In this paper an automatic plantar ROIs detection method using a customized low-cost pressure acquisition device is proposed. Plantar pressure data and 3D motion capture data were collected from 28 subjects （14 healthy subjects and 14 subjects with hallux valgus）. The maximal inter-frame difference during the stance phase was calculated. Consequently, the ROIs were defined by the first-order difference in combination with prior anatomic knowl- edge. The anatomic locations were determined by the maximal inter-frame difference and second maximal inter-frame differ- ence, which nearly coincided. Our system can achieve average recognition accuracies of 92.90%, 89.30%, 89.30%, 92.90%, 92.90%, and 89.30% for plantar ROIs hallux and metatarsi I-V, respectively, as compared with the annotations using the 3D motion capture system. The maximal difference of metatarsus heads II-V, and the impulse of the medial and lateral heel features made a significant contribution to the classification ofhallux valgus and healthy subjects with ≥ 80% sensitivity and specificity. Furthermore, the plantar pressure acquisition system is portable and convenient to use, thus can be used in home- or commu- nity-based healthcare applications.
