Skip to content
Free planNo credit card requiredStart writing
AI for Research home
AI for Research home
Dashboard
Sign inGet started

Search 250 million research papers

Read the abstract, see who wrote it and who cites it, and get the citation in APA, MLA, Chicago or Harvard.

About 9,705 papers for “Inter frame”

Video Inter-Frame Forgery Detection

Xuan Hau Nguyen · Data Archiving and Networked Services (DANS) · 2019

This data-set was used in experiments of the paper "Detecting Video Inter-Frame Forgeries Based on Convolutional Neural Network Model"

Cited by 0Open access

Inter-Frame Field Unification (IFFU)

Brando, Audric · PhilPapers (PhilPapers Foundation) · 2025

We present Inter-Frame Field Unification (IFFU), a compatibility-based framework for unifying fundamental forces. Building on our earlier work in Interpolative Physics and its formal equations, this theory models spacetime not as a collapsing or geometric structure, but as an interpolative medium—capable of sustaining coherent signal identity across phase-shifting frames. A scalar constant: K. K governs the limits of this coherence, predicting when interactions remain stable or collapse. IFFU formalizes how gravity, electromagnetism, and nuclear forces emerge as different expressions of frame compatibility under dynamic conditions. It offers a complete, testable set of equations linking mass-energy, temporal displacement, and resonance. Designed with practical experimentation in mind, this model enables applications in entanglement analysis, quark-phase stabilization, and localized gravitational simulation. As the synthesis of our previous two papers, IFFU provides a structured and lab-ready path toward unified field modeling.

Cited by 0Open access

Inter-frame Motion Correction for

Mr Thermometry, S. Suprijanto, M. W. Vogel et al. · 2015

Abstract. Noninvasive temperature measurement is feasible with MRI to monitor changes in thermal therapy. Phase shift based MR thermome-try gives an estimate of the relative temperature variation between ther-mal and baseline images. This technique is limited, however, when ap-plied on targets under inter-frame motion. Simple image registration and subtraction are not adequate to recover the temperature properly since the phase shift due to temperature changes is corrupted by an unwanted phase shift. In this work, the unwanted phase shift is predicted from the raw registered phase shift map itself. To estimate the unwanted phase shift, a thin plate smoothing spline is fitted to the values outside the heated region. The spline value in the heated area serves as an estimate for the offset. The estimation result is applied to correct errors in the temperature maps of an ex-vivo experiment. 1

Cited by 0

Intra-frame deblurring by leveraging inter-frame camera motion

Haichao Zhang, Shuicheng Yan · 2015

Camera motion introduces motion blur, degrading the quality of video. A video deblurring method is proposed based on two observations: (i) camera motion within capture of each individual frame leads to motion blur; (ii) camera motion between frames yields inter-frame mis-alignment that can be exploited for blur removal. The proposed method effectively leverages the information distributed across multiple video frames due to camera motion, jointly estimating the motion between consecutive frames and blur within each frame. This joint analysis is crucial for achieving effective restoration by leveraging temporal information. Extensive experiments are carried out on synthetic data as well as real-world blurry videos. Comparisons with several state-of-the-art methods verify the effectiveness of the proposed method.

Cited by 37

SinoCor: Inter-frame and intra-frame motion correction tool

Daniel Eiland, Debasis Mitra, Mahmoud A. Abdalah et al. · 2012

SinoCor, a body-motion detection and correction tool for nuclear imaging has been developed. It is currently provided as a JAVA-based plug-in for <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ImageJ</i> for use with data acquired via Single Photon Emission Computed Tomography (SPECT) scans. SinoCor works only in the sinogram space without going through any back-projection operation. It provides automatic correction for both interframe and intra-frame motion. Inter-frame motion occurs if the subject shifts location in-between two frame acquisitions during the tomographic imaging. The intra-frame motion happens when the shift occurs when a particular frame is being acquired.

Cited by 3

Inter-Frame Similarity based Video Transcoding

R. Balsree, Agness Thawani, S. Gopalan et al. · 2006

Multimedia services over wireless networks were made popular by the arrival of smart handhelds. These devices bring heterogeneity to the wireless networks and to the content creation as the content cannot be delivered in its original format due to the difference in the capabilities of these handhelds. An intermediate stage of processing like transcoding is carried out before delivering multimedia content. Under certain scenarios, it is required to convert the content attributes such as bit rate, frame rate, etc. while still retaining the content format to cater to devices with varying capabilities. We propose an algorithm that prioritizes frames taking into account inter frame similarity to perform frame dropping. The priority value based frame dropping in turn aids in delivering better quality video. Our frame priority assignment algorithm is based on uniform distribution of dropped frames to minimize jitter and maximizing the distance between two consecutive dropped frames.

Cited by 3

Normalization of the inter-frame inform

J. C. Segura · 2015

A filter that introduces inter-frame information into the voice fea-tures set is proposed in this paper. The filter adds the autocor-relations of the cepstral coefficients to the set of characteristics used for training and recognition. Those autocorrelations should not depend on the environment conditions. Because they should only depend on the information to recognize, a normalization of that inter-frame information is convenient. The filter defined im-plements this normalization by transforming the autocorrelations into a normalized domain defined with clean adaptation data. This temporal processing of the features is added to the Histogram Equalization of the cepstral coefficients (HEQ) used to normal-ize the MFCCs. An analysis is done about the most effective do-main (original MFCCS or equalized MFCCs) on which the tem-poral processing should be executed. Performance results for the proposed algorithm are presented for AURORA2 and AURORA4 databases. Index Terms: robust speech recognition, temporal filtering, frames correlation

Cited by 0

Inter-Symbol Interference Aware Frame Synchronization

Roberto Pedone, M. Villanti, Giovanni Emanuele Corazza · 2006

Frame synchronization is conventionally intended as "epoch recovery" of a symbols synchronous stream. But, what happens when symbol timing is unknown? A typical approach to this problem involves oversampling, which is computational intensive. This paper introduces a novel alternative approach whereby the detector is made aware of the emerging ISI due to imperfect symbol timing recovery in order to achieve the wanted performance with low computational complexity. The resulting sequence, identified as ISI-UW, is obtained as the combination of several conventional UW appropriately shifted in time. The adoption of this particular sequence structure allows to enhance performance in the worst case scenario, at the cost of a slight performance loss in the ideal case, and reveals to be an interesting low-complexity alternative to conventional oversampling techniques to cope with symbol timing fractional misalignments

Cited by 0

Inter-Frame Differencing in Training Data for Artificial Intelligence : Contour Processing for Inter-Frame Differencing Method

Yuan Enze, Yasuyuki Miura · 2020

We investigate the frame subtraction method in the research of the security surveillance system for old people by artificial intelligence using deep neural networks. The results in low-illumination images become smaller when the conventional inter-frame differencing method is applied. Therefore, we propose an optimal method of inter-frame differencing in various illuminance environments. The accuracy of inter-frame differencing improves when the proposed method using contour processing is applied.

Cited by 3

Joint inter-frame and intra-frame predictive coding of LSF parameters

Saikat Chatterjee, T.V. Sreenivas · 2007

We explore the performance of two dimensional (2-D) prediction based LSF quantization method for both wide-band and telephone-band (narrow-band) speech. The 2-D prediction based method exploits both the inter-frame and intra-frame correlations of LSF parameters. We show that a 4th order 2-D predictor provides optimum prediction gain as well as improved quantization performance at various choices of frame shift for both wide-band and telephone-band speech. Existing one dimensional (1-D) predictive method, exploiting only inter-frame correlation, results in poor performance at larger frame shifts; whereas proposed 2-D predictor provides lower spectral distortion as well as lower number of outliers compared to existing memory-based and memory-less methods.

Cited by 0

Combining Intra-Frame With Inter-Frame Hardware Adaptations To Save Energy

Ruchira Sasanka · 2002

We consider the use of dynamic voltage/frequency scaling (DVS) and architectural adaptation for saving energy for realtime multimedia applications. Previous work has considered this problem by invoking architectural and voltage/frequency adaptations at the granularity of a full frame of multimedia applications. The proposed inter-frame adaptation algorithm exploited computation slack in each frame by using the lowest energy configuration that still meets the application deadline. We make two sets of contributions: (1) We explore architectural adaptation within a frame, or intra-frame adaptations, using both old algorithms proposed in the context of non-real-time applications and new algorithms. While inter-frame architectural adaptations can slow the computation, the intra-frame algorithms attempt to save energy without affecting performance. (2) We show how intra-frame and inter-frame architectural adaptations can be combined, and compare pure inter-frame, pure intra-frame, and the combined approaches. We find that intra-frame architectural adaptation is effective for realtime multimedia applications. However, the combined inter-frame and intra-frame architectural adaptation approach saves more energy than either technique alone for systems both without and with support for inter-frame controlled DVS. Without DVS, inter-frame architectural adaptation provides most of the benefits, but with less slack intra-frame is more beneficial. With DVS, intra-frame architectural adaptation provides most of the benefits. However, it is not best for all applications, and, furthermore, the overhead for implementing inter-frame architectural adaptation in a system with inter-frame DVS support is small. Therefore, for systems both without and with DVS, our results indicate that the co...

Cited by 0

Combined Inter-frame and Inter-color Prediction for Color Video Denoising

Jingjing Dai, Oscar C. Au, Chao Pang et al. · 2012

An advanced color video denoising scheme which we call CIFIC based on combined inter-frame and inter-color prediction is presented in this paper. CIFIC performs the denoising filtering in the RGB color space, and exploits both the inter-frame and inter-color correlation in color video signal directly by forming multiple predictors for each color component using all three color components in the current frame as well as the motion-compensated neighboring reference frames. The temporal correspondence is established through the joint-RGB noise-robust motion estimation (ME) which acquires a single motion trajectory for the RGB components. Then the current noisy observation as well as the inter-frame and inter-color predictors are combined by a linear minimum mean squared error (LMMSE) filter to obtain the denoised estimate for every color component. The experimental results verify that CIFIC provides competitive performance both in terms of the objective metric and in perceptual quality when compared with other state-of-the-art algorithms.

Cited by 2

Neural Inter-Frame Compression for Video Coding

Abdelaziz Djelouah, Joaquim Campos, Simone Schaub-Meyer et al. · 2019

While there are many deep learning based approaches for single image compression, the field of end-to-end learned video coding has remained much less explored. Therefore, in this work we present an inter-frame compression approach for neural video coding that can seamlessly build up on different existing neural image codecs. Our end-to-end solution performs temporal prediction by optical flow based motion compensation in pixel space. The key insight is that we can increase both decoding efficiency and reconstruction quality by encoding the required information into a latent representation that directly decodes into motion and blending coefficients. In order to account for remaining prediction errors, residual information between the original image and the interpolated frame is needed. We propose to compute residuals directly in latent space instead of in pixel space as this allows to reuse the same image compression network for both key frames and intermediate frames. Our extended evaluation on different datasets and resolutions shows that the rate-distortion performance of our approach is competitive with existing state-of-the-art codecs.

Cited by 182

Neural Reference Synthesis for Inter Frame Coding

Dandan Ding, Xiang Gao, Chenran Tang et al. · IEEE Transactions on Image Processing · 2021

This work proposes the neural reference synthesis (NRS) to generate high-fidelity reference block for motion estimation and motion compensation (MEMC) in inter frame coding. The NRS is comprised of two submodules: one for reconstruction enhancement and the other for reference generation. Although numerous methods have been developed in the past for these two submodules using either handcrafted rules or deep convolutional neural network (CNN) models, they basically deal with them separately, resulting in limited coding gains. By contrast, the NRS proposes to optimize them collaboratively. It first develops two CNN-based models, namely EnhNet and GenNet. The EnhNet only uses spatial correlations within the current frame for reconstruction enhancement and the GenNet is then augmented by further aggregating temporal correlations across multiple frames for reference synthesis. However, a direct concatenation of EnhNet and GenNet without considering the complex temporal reference dependency across inter frames would implicitly induce iterative CNN processing and cause the data overfitting problem, leading to visually-disturbing artifacts and oversmoothed pixels. To tackle this problem, the NRS applies a new training strategy to coordinate the EnhNet and GenNet for more robust and generalizable models, and also devises a lightweight multi-level R-D (rate-distortion) selection policy for the encoder to adaptively choose reference blocks generated from the proposed NRS model or conventional coding process. Our NRS not only offers state-of-the-art coding gains, e.g., >10% BD-Rate (Bjøntegaard Delta Rate) reduction against the High Efficiency Video Coding (HEVC) anchor for a variety of common test video sequences encoded at a wide bit range in both low-delay and random access settings, but also greatly reduces the complexity relative to existing learning-based methods by utilizing more lightweight DNNs. All models are made publicly accessible at https://github.com/IVC-Projects/NRS for reproducible research.

Cited by 9

Speed estimation based on inter-frame difference

Huawei Xie · 2024

Not all the physical evidence and traces left by field accidents are necessarily related to the occurrence of accidents and the identification of speed. Later appraisers also need to carry out the reconstruction of traffic accidents through the analysis of these evidence. Therefore, the traditional methods for the identification of speed of field road traffic accidents are generally complicated and not accurate enough. Therefore, Inter-frame Difference calculation method is more convenient, quick and accurate in the actual traffic accident case handling.

Cited by 0