Backward Playback Research Articles

Language Lateralization by Passive Auditory fMRI in Presurgical Assessment for Temporal Lobe Epilepsy: A Single-Center Retrospective Study.

Background: In temporal lobe epilepsy (TLE), estimating the potential risk of language dysfunction before surgery is a necessary procedure. Functional MRI (fMRI) is considered the most useful to determine language lateralization noninvasively. However, there are no standardized language fMRI protocols, and several issues remain unresolved. In particular, the language tasks normally used are predominantly active paradigms that require the overt participation of patients, making assessment difficult for pediatric patients or patients with intellectual disabilities. In this study, task-based fMRI with passive narrative listening was applied to evaluate speech comprehension to estimate language function in Japanese-speaking patients with drug-resistant TLE. Methods: Twenty-one patients (six with intellectual disabilities) participated. Patients listened to passive auditory stimuli with combinations of forward and silent playback, and forward and backward playback. The activation results were extracted using a block design, and lateralization indices were calculated. The obtained fMRI results were compared to the results of the Wada test. Results: The concordance rate between fMRI and the Wada test was 95.2%. Meaningful responses were successfully obtained even from participants with intellectual disabilities. Conclusions: This passive fMRI paradigm can provide safe and easy presurgical language evaluation, particularly for individuals who may not readily engage in active paradigms.

New pixel based approach for reverse play of MPEG video for streaming system

In macroblock based architecture of MPEG video streaming system with backward playback support, the macroblocks of the frames are divided into two categories: Backward Macroblock (BMB) and Forward/Backward Macroblock (FBMB). The BMB and FBMB are processed differently. This approach reduces the network bandwidth and buffer size requirements. In this paper, we propose a pixel based approach that accesses less data from the server and hence further saves the network bandwidth and buffer requirement. The I- or P-frame (say, frame n−1) is reverse-predicted from the currently decoded frame (i.e., frame n) that is stored in the frame buffer at the client system. Using the motion vector information of frame n, the positions of its various pixels are found in the frame n−1 and their exact values are found using the prediction errors of the frame n by just subtracting them from their values in the frame n. Thus, most of the pixels of frame n−1 are predicted from the frame n. Experimental results show that on an average 93.4% of pixels in the previous I- or P-frame can be reverse-predicted from the current P-frame. The rest 6.6% unpredicted pixels are accumulated in the form of blocks and those blocks are requested from the server. We also propose new Block Identification Algorithms to identify different blocks of unpredicted pixels in an image. They are Maximum Height Minimum Width (MHMW), First Come First Serve (FCFS), Maximum Area (MA), and Biggest Block (BB) algorithms. The server processes the MPEG video stream and returns the desired blocks. We also discuss a FindBlock algorithm for extracting a small block of any frame from the MPEG video stream. Thus, only the motion vectors, prediction errors of frame n, and the unpredicted pixels of the frame n−1 need to be transmitted to the client system. This makes considerable saving in system resources.

JPEG2000-Based Scalable Interactive Video (JSIV) With Motion Compensation

In a recent work, the authors proposed a novel paradigm for interactive video streaming and coined the term JPEG2000-Based Scalable Interactive Video (JSIV) for it. In this work, we investigate JSIV when motion compensation is employed to improve prediction, something that was intentionally left out in our earlier treatment. JSIV relies on three concepts: storing the video sequence as independent JPEG2000 frames to provide quality and spatial resolution scalability, prediction and conditional replenishment of code-blocks to exploit inter-frame redundancy, and loosely coupled server and client policies in which a server optimally selects the number of quality layers for each code-block transmitted and a client makes the most of the received (distorted) frames. In JSIV, the server transmission problem is optimally solved using Lagrangian-style rate-distortion optimization. The flexibility of JSIV enables us to employ a wide variety of frame prediction arrangements, including hierarchical B-frames. JSIV provides considerably better interactivity compared with existing schemes and can adapt immediately to interactive changes in client interests, such as forward or backward playback and zooming into individual frames. Experimental results show that JSIV's performance is inferior to that of SVC in conventional streaming applications while JSIV performs better in interactive browsing applications.

JPEG2000-Based Scalable Interactive Video (JSIV)

We propose a novel paradigm for interactive video streaming and we coin the term JPEG2000-based scalable interactive video (JSIV) for it. JSIV utilizes JPEG2000 to independently compress the original video sequence frames and provide for quality and spatial resolution scalability. To exploit interframe redundancy, JSIV utilizes prediction and conditional replenishment of code-blocks aided by a server policy that optimally selects the number of quality layer for each code-block transmitted and a client policy that makes most of the received (distorted) frames. It is also possible for JSIV to employ motion compensation; however, we leave this topic to future work. To optimally solve the server transmission problem, a Lagrangian-style rate-distortion optimization procedure is employed. In JSIV, a wide variety of frame prediction arrangements can be employed including hierarchical B-frames of the scalable video coding (SVC) extension of the H.264/AVC standard. JSIV provides considerably better interactivity compared to existing schemes and can adapt immediately to interactive changes in client interests, such as forward or backward playback and zooming into individual frames. Experimental results for surveillance footage, which does not suffer from the absence of motion compensation, show that JSIV's performance is comparable to that of SVC in some usage scenarios while JSIV performs better in others.

New Architecture for MPEG Video Streaming System With Backward Playback Support

MPEG digital video is becoming ubiquitous for video storage and communications. It is often desirable to perform various video cassette recording (VCR) functions such as backward playback in MPEG videos. However, the predictive processing techniques employed in MPEG severely complicate the backward-play operation. A straightforward implementation of backward playback is to transmit and decode the whole group-of-picture (GOP), store all the decoded frames in the decoder buffer, and play the decoded frames in reverse order. This approach requires a significant buffer in the decoder, which depends on the GOP size, to store the decoded frames. This approach could not be possible in a severely constrained memory requirement. Another alternative is to decode the GOP up to the current frame to be displayed, and then go back to decode the GOP again up to the next frame to be displayed. This approach does not need the huge buffer, but requires much higher bandwidth of the network and complexity of the decoder. In this paper, we propose a macroblock-based algorithm for an efficient implementation of the MPEG video streaming system to provide backward playback over a network with the minimal requirements on the network bandwidth and the decoder complexity. The proposed algorithm classifies macroblocks in the requested frame into backward macroblocks (BMBs) and forward/backward macroblocks (FBMBs). Two macroblock-based techniques are used to manipulate different types of macroblocks in the compressed domain and the server then sends the processed macroblocks to the client machine. For BMBs, a VLC-domain technique is adopted to reduce the number of macroblocks that need to be decoded by the decoder and the number of bits that need to be sent over the network in the backward-play operation. We then propose a newly mixed VLC/DCT-domain technique to handle FBMBs in order to further reduce the computational complexity of the decoder. With these compressed-domain techniques, the proposed architecture only manipulates macroblocks either in the VLC domain or the quantized DCT domain resulting in low server complexity. Experimental results show that, as compared to the conventional system, the new streaming system reduces the required network bandwidth and the decoder complexity significantly.