Adaptive Frame Rate Research Articles

Enabling Adaptive Cloud Gaming in an Open-Source Cloud Gaming Platform

We study the problem of optimally adapting ongoing cloud gaming sessions to maximize the gamer experience in dynamic environments. The considered problem is quite challenging because: 1) gamer experience is subjective and hard to quantify; 2) the existing open-source cloud gaming platform does not support dynamic reconfigurations of video codecs; and 3) the resource allocation among concurrent gamers leaves a huge room to optimize. We rigorously address these three challenges by: 1) conducting a crowdsourced user study over the live Internet for an empirical gaming experience model; 2) enhancing the cloud gaming platform to support frame rate and bitrate adaptation on-the-fly; and 3) proposing optimal yet efficient algorithms to maximize the overall gaming experience or ensure the fairness among gamers. We conduct extensive trace-driven simulations to demonstrate the merits of our algorithms and implementation. Our simulation results show that the proposed efficient algorithms: 1) outperform the baseline algorithms by up to 46% and 30%; 2) run fast and scale to large (≤8000 gamers) problems; and 3) achieve the user-specified optimization criteria, such as maximizing average gamer experience or maximizing the minimum gamer experience. The resulting cloud gaming platform can be leveraged by many researchers, developers, and gamers.

Mo1589 Role of Second-Generation Colon Capsule Endoscopy for Whole Gut Evaluation

although colon capsule endoscopy (CCE) was developed for evaluation of the colon, it can be used to assess the entire GI tract since it offers excellent images also of the esophagus and the small bowel (SB), with the exception of the stomach that remains poorly evaluated. Usually, after the firsts 3 min of running, CCE slows down the frame rate to 14 images/min. When SB is detected CCE automatically restarts using the Adaptive Frame Rate (AFR) technology. Nevertheless, CCE can be also “activated” to the AFR mode prior to the ingestion allowing the whole gut evaluation at a high frame rate acquisition.

English

There are large range of applications such as disaster management, military and security that has drawn attention of researches to this type of networks. There are large issues in WSNs like battery consumption, packet loss, path loss, interference issues, bit error rate and clustering. There are many algorithms and techniques that are used to reduce these issues. In this paper we introduced new technique which is based upon cross layer frame rate adaptation scheme to prevent the energy consumption. This proposed technique is much better than existing technique. It implemented using NS -2.

Monocular camera and IMU integration for indoor position estimation.

This paper presents a monocular camera (MC) and inertial measurement unit (IMU) integrated approach for indoor position estimation. Unlike the traditional estimation methods, we fix the monocular camera downward to the floor and collect successive frames where textures are orderly distributed and feature points robustly detected, rather than using forward oriented camera in sampling unknown and disordered scenes with pre-determined frame rate and auto-focus metric scale. Meanwhile, camera adopts the constant metric scale and adaptive frame rate determined by IMU data. Furthermore, the corresponding distinctive image feature point matching approaches are employed for visual localizing, i.e., optical flow for fast motion mode; Canny Edge Detector & Harris Feature Point Detector & Sift Descriptor for slow motion mode. For superfast motion and abrupt rotation where images from camera are blurred and unusable, the Extended Kalman Filter is exploited to estimate IMU outputs and to derive the corresponding trajectory. Experimental results validate that our proposed method is effective and accurate in indoor positioning. Since our system is computationally efficient and in compact size, it's well suited for visually impaired people indoor navigation and wheelchaired people indoor localization.

Ensuring QoS with Adaptive Frame Rate and Feedback Control Mechanism in Video Streaming

Video over best-effort packet networks is cumbered by a number of factors including unknown and timevarying bandwidth, delay and losses, as well as many additional issues such as how to fairly share the network resources amongst many flows and how to efficiently perform one-to-many communication for popular content. This research investigates video streaming formats, encoding and compression techniques towards the development and simulation of a rate adaptation model to reduce packet loss. The thrust of this research aimed at enriching and enhancing the quality of video streaming over the wireless network. We developed both mathematical models which were thereafter simulated to depict the need for advancing the existing solution for packet scheduling towards recovery from packet loss and error handling in video streaming.Keywords: Quantity of Service (QOS), Adaptive Frame Rate, Video Streaming

A 135 MHz 542 k Gates High Throughput H.264/AVC Scalable High Profile Decoder

To satisfy the requirement of application heterogeneities, the latest H.264/AVC based video coding standard called scalable video coding additional includes temporal, SNR, and spatial scalabilities for frame rate, quality, and frame resolution adaptation. However, these inclusions significantly increase chip design difficulties such as decoding time, memory bandwidth, and area cost. This paper presents an H.264/AVC scalable high profile decoder realization with several optimization techniques to provide high throughput video decoding. For decoding flow, this paper proposes an one-pass macroblock-based quality layer decoding flow for SNR scalability and 71% of external memory bandwidth and 66% of macroblock processing cycles can be saved. For texture padding in interlayer intra prediction, the modified padding flow can save 26% of decoding time. For interlayer predictor design, this paper proposes a centralized concept for accumulation-based calculation of corresponding spatial position, simplified poly-phase interpolator, and efficient motion vector generator to save area cost and decoding time. Furthermore, the residual reconstruction path with the parallel-pipeline architecture is also proposed to cope with the additional decoding complexity and thus leads to 54% of gate count savings compared to the traditional serial-pipeline architecture. Finally, the proposed H.264/AVC scalable high profile decoder design is implemented with 90 nm CMOS technology and it costs 542 k gate count and 39.66 Kbytes on-chip memory while is capable to decode 60 frames/s for resolution with three quality layers at 135 MHz operating frequency.

10.3: Ultra low‐power Electrowetting‐based Displays Using Dynamic Frame Rate Driving

AbstractPortable multi‐media devices with electrowetting‐based displays take advantage of the supreme optical performances and of the video capabilities of the screen. As described in this paper these displays benefit from the implementation of dynamic adaptive frame rate driving schemes, resulting in ultra‐low power consumption and extended battery life while maintaining the high level of image quality.

Capsule endoscopy compared with conventional colonoscopy for detection of colorectal neoplasms

Colon capsule endoscopy (CCE) may be a means to overcome the low adherence to colorectal cancer screening. The device is an ingestible capsule with a video camera at both ends that can take photographs as it progresses through the gastrointestinal tract. PillCam colon (PCC1) may be used for structural evaluation of the large bowel following an adequate cleaning procedure. PCC1 measures 11 mm × 31 mm and has dual cameras that enable the device to acquire video images from both ends with a wide coverage area, automatic light control and a frame rate of four frames per second. The system includes a sensor array and data recorder connected to the patient during the procedure. The recorded data are downloaded to the Given Imaging Rapid workstation for review of the colon video. The second generation of PillCam Colon (PCC2) is similar to PCC1 and incorporates new developments. The angle of view has been increased to 172 degrees. It has an adaptive frame rate, alternating from 35 frames per second while in motion to 4 images when virtually stationary. The new RAPID(®) software now includes a simple graphic interface tool for polyp size estimation. The procedure of bowel cleansing until capsule ingestion is similar to that used for traditional colonoscopy. However it is more rigorous as the bowel cleanliness for capsule colonoscopy has to be excellent or at least good to result in an adequate sensitivity of the method. Briefly, it consists of 3.5-4 L of split dose polyethylene glycol. Oral NaP boosters are administered after 1-2 h if the capsule has entered the small bowel. Sodium phosphate (NaP) seems to be a necessary adjunct to the regimen because the total transit time is doubled without NaP. The cleansing level was considered to be good to excellent in 72%-88% in studies with PCC1. The sensitivity for significant polyps (> 6 mm or more than 3 polyps >3 mm) ranged from 63%-88% with specificities between 64%-94%. PCC2 showed an improved sensitivity of 89% and a specificity of 76%. CCE seems to be a safe and effective method of visualizing the colonic mucosa through colon fluids without the need for sedation or insufflation of air. The sensitivity of CCE to detect polyps, advanced adenomas and cancer is lower compared to optical colonoscopy but improvements will be made in the near future. With an increased recording duration, even a panenteric examination of the whole gastrointestinal tract may be possible.

Design of Real-Time Self-Frame-Rate-Control Foreground Detection for Multiple Camera Surveillance System

Emerging video surveillance technologies are based on foreground detection to achieve event detection automatically. Integration foreground detection with a modern multi-camera surveillance system can significantly increase the surveillance efficiency. The foreground detection often leads to high computational load and increases the cost of surveillance system when a mass deployment of end cameras is needed. This paper proposes a DSP-based foreground detection algorithm. Our algorithm incorporates a temporal data correlation predictor (TDCP) which can exhibit the correlation of data and reduce computation based on this correlation. With the DSP-oriented foreground detection, an adaptive frame rate control is developed as a low cost solution for multi-camera surveillance system. The adaptive frame rate control automatically detects the computational load of foreground detection on multiple video sources and adaptively tunes the TDCP to meet the real-time specification. Therefore, no additional hardware cost is required when the number of deployed cameras is increased. Our method has been validated on a demonstration platform. Performance can achieve real-time CIF frame processing for a 16-camera surveillance system by single-DSP chip. Quantitative evaluation demonstrates that our solution provides satisfied detection rate, while significantly reducing the hardware cost.

Adaptive frame rate up-conversion based on motion classification

In this paper, a new technique on video frame rate up-conversion (FRUC) is presented by combining the adaptive motion classification (AMC) for image sequences and the mixed motion estimation (ME). In the proposed FRUC scheme, the AMC classifies sequences into global and local motion sequences (G/LMS) whose advantages are fully utilized. The mixture of bidirectional ME (BDME) and unidirectional ME (UDME) is proposed to avoid hole and “background replace object” phenomenon in interpolated frames. Moreover, the motion vectors (MVs) refinement technique is employed to smooth MVs field. For LMS, the motion detection is used to deal with static background and occlusions are located by using forward prediction of motion regions. Correctional sum of absolute difference (CSAD) which gives more precise physical MVs field than conventional SAD is applied during all of the ME process. Simulation results demonstrate the effectiveness of the proposed FRUC algorithm.

P‐48: Adaptive Frame Rate Up‐Conversion Considering Low Computational Complexity and Complex Motion

AbstractThis paper presents a new method for frame rate up‐conversion using sub‐sampled bilateral motion estimation, motion vector smoothing, simplified bidirectional motion compensated interpolation, and complex motion detection. The proposed method produces improved image quality and requires less computational complexity compared to conventional motion estimation. The average PSNRs of the proposed method for frame rate up‐conversion outperform those of the benchmark frame rate up‐conversion technique by up to 4.39 dB for the test sequences. Furthermore, the motion estimation of the proposed FRUC method reduces the required computational complexity to 12.5% of that required for full‐search block matching motion estimation.