Shadan Khattak

Bio: Shadan Khattak is an academic researcher from King Faisal University. The author has contributed to research in topics: Multiview Video Coding & Coding tree unit. The author has an hindex of 5, co-authored 10 publications receiving 67 citations. Previous affiliations of Shadan Khattak include De Montfort University & COMSATS Institute of Information Technology.

Sensor Fusion for Identification of Freezing of Gait Episodes Using Wi-Fi and Radar Imaging

Abstract: Parkinson’s disease (PD) is a progressive and neurodegenerative condition causing motor impairments One of the major motor related impairments that present biggest challenge is freezing of gait (FOG) in Parkinson’s patients In FOG episode, the patient is unable to initiate, control or sustain a gait that consequently affects the Activities of Daily Livings (ADLs) and increases the occurrence of critical events such as falls This paper presents continuous monitoring ADLs and classification freezing of gait episodes using Wi-Fi and radar imaging The idea is to exploit the multi-resolution scalograms generated by channel state information (CSI) imprint and micro-Doppler signatures produced by reflected radar signal A total of 120 volunteers took part in experimental campaign and were asked to perform different activities including walking fast, walking slow, voluntary stop, sitting down & stand up and freezing of gait Two neural networks namely Autoencoder and a proposed enhanced Autoencoder were used classify ADLs and FOG episodes using data fusion process by combining the images acquired from both sensing techniques The Autoencoder provided overall classification accuracy of ~87% for combined datasets The proposed algorithm provided significantly better results by presenting an overall accuracy of ~98% using data fusion

Temporal and Inter-View Consistent Error Concealment Technique for Multiview Plus Depth Video

Abstract: Multiview plus depth (MVD) is an emerging video format with many applications, including 3-D television and free viewpoint television. During the broadcast of a compressed MVD video, transmission errors may cause the loss of whole frames, resulting in significant degradation of video quality. Error concealment techniques have been widely used to deal with transmission errors in video communication. However, the existing solutions do not address the requirement that the reconstructed frames should be consistent with neighboring frames, i.e., corresponding pixels should have consistent color information. We propose a new consistency model for error concealment of MVD video that allows one to maintain a high level of consistency between frames of the same view (temporal consistency) and those of neighboring views (inter-view consistency). We then propose an algorithm that uses our model to implement concealment in a consistent way. Simulations with the reference software for the multiview video coding project of the joint video team of the ISO/IEC MPEG and ITU-T VCEG show that our method outperforms benchmark techniques, including a baseline approach based on the boundary matching algorithm, with respect to both reconstruction quality and view consistency.

Fast encoding techniques for Multiview Video Coding

Abstract: Multiview Video Coding (MVC) is a technique that permits efficient compression of multiview video. MVC uses variable block size motion and disparity estimation for block matching. This requires an exhaustive search process that involves all possible macro-block partition sizes. We analyze the time complexity of MVC and the methods that have been proposed to speed up motion and disparity estimation. We then propose two new methods: Previous Disparity Vector Disparity Estimation (PDV-DE) and Stereo-Motion Consistency Constraint Motion and Disparity Estimation (SMCC-MDE). PDV-DE exploits the correlation between temporal levels and disparity vectors to speed up the disparity estimation process while SMCC-MDE exploits the geometrical relationship of consecutive frame pairs to speed up motion and disparity estimation. We build a complete low complexity MVC encoding solution that combines our two methods with complementary previous methods to speed up motion and disparity search. We evaluate the complexity of our solution in terms of encoding time and number of search points. Our experimental results show that our solution can reduce the encoding time and number of search points of the standard MVC implementation (JMVM 6.0) using the fast TZ search mode up to 93.7% and 96.9%, respectively, with negligible degradation in the rate-distortion performance. Compared to the best published results, this is an improvement of up to 11% and 7%, respectively. (C) 2013 Elsevier B.V. All rights reserved.

Low-complexity multiview video coding

Abstract: We consider the problem of complexity reduction in Multiview Video Coding (MVC). We provide a unique comprehensive study that integrates and compares the different low complexity encoding techniques that have been proposed at different levels of the MVC system. In addition, we propose a novel complexity reduction method that takes advantage of the relationship between disparity vectors along time. The relationship is exploited with respect to the motion activity in the frame, as well as with the position of the frame in the Group of Pictures. We integrate this technique into our unique comprehensive framework and evaluate the performance of the resulting system in different setups. We show that the effective combination of complexity reduction techniques results in saving up to 93% in encoding time at the cost of only 0.08 dB in peak signal-to-noise ratio (PSNR) and 1.64% increase in bitrate compared to the standard MVC implementation (JMVM 6.0).

Early decision of CU splitting, using base view information, for low complexity MV-HEVC

Abstract: Multi-view video is becoming a new trend in the multimedia industry Due to large amount of data generated by such videos, efficient compression and fast encoding speed are hot research areas Recently MV-HEVC, the multi-view extension of High Efficiency Video Coding (HEVC) standard has been introduced It improves the coding efficiency but the encoding complexity has increased In this paper we propose an early coding unit (CU) splitting decision of the dependent views from the coding tree units (CTUs) depth information of the base view Maximum depth of the CU (dependent views) is limited to the maximum value of the depths of the eight neighboring CTUs of the co-located CTU in the base view Experimental results reveal that our proposed technique achieves upto 6308% reduction in encoding time, when compared with HTM reference software

IST project ATTEST - an evolutionary and optimised approach on 3D-TV

Abstract: In this paper we will present the concept of a system that allows for an evolutionary introduction of depth perception into the existing 2D digital TV framework. The work is part of the European Information Society Technologies (IST) project “Advanced Three-Dimensional Television System Technologies” (ATTEST), an activity where industries, research centers and universities have joined forces to design a backwardscompatible, flexible and modular broadcast 3D-TV system, where all parts of the 3D processing chain are optimised to one another. This includes content creation, coding and transmission, display and research in human 3D perception, which be will used to guide the development process. The goals of the project comprise the development of a novel broadcast 3D camera, algorithms to convert existing 2D-video material into 3D, a 2Dcompatible coding and transmission scheme for 3D-video using MPEG2/4/7 technologies and the design of two new autostereoscopic displays.

A Hybrid Frame Concealment Algorithm for H.264/AVC | NIST

Abstract: In packet-based video transmissions, packets loss due to channel errors may result in the loss of the whole video frame. Recently, many error concealment algorithms have been proposed in order to combat channel errors; however, most of the existing algorithms can only deal with the loss of macroblocks and are not able to conceal the whole missing frame. In order to resolve this problem, in this paper, we have proposed a new hybrid motion vector extrapolation (HMVE) algorithm to recover the whole missing frame, and it is able to provide more accurate estimation for the motion vectors of the missing frame than other conventional methods. Simulation results show that it is highly effective and significantly outperforms other existing frame recovery methods.

Initialization, Limitation, and Predictive Coding of the Depth and Texture Quadtree in 3D-HEVC

Abstract: The 3D video extension of High Efficiency Video Coding (3D-HEVC) exploits texture-depth redundancies in 3D videos using intercomponent coding tools. It also inherits the same quadtree coding structure as HEVC for both components. The current software implementation of 3D-HEVC includes encoder shortcuts that speed up the quadtree construction process, but those are always accompanied by coding losses. Furthermore, since the texture and its associated depth represent the same scene, at the same time instant and view point, their quadtrees are closely linked. In this paper, an intercomponent tool is proposed in which this link is exploited to save both runtime and bits through a joint coding of the quadtrees. If depth is coded before the texture, the texture quadtree is initialized from the coded depth quadtree. Otherwise, the depth quadtree is limited to the coded texture quadtree. A 31% encoder runtime saving, a -0.3% gain for coded and synthesized views and a -1.8% gain for coded views are reported for the second method.

A Review of the State of the Art in Non-Contact Sensing for COVID-19

Abstract: COVID-19, caused by SARS-CoV-2, has resulted in a global pandemic recently. With no approved vaccination or treatment, governments around the world have issued guidance to their citizens to remain at home in efforts to control the spread of the disease. The goal of controlling the spread of the virus is to prevent strain on hospitals. In this paper, we focus on how non-invasive methods are being used to detect COVID-19 and assist healthcare workers in caring for COVID-19 patients. Early detection of COVID-19 can allow for early isolation to prevent further spread. This study outlines the advantages and disadvantages and a breakdown of the methods applied in the current state-of-the-art approaches. In addition, the paper highlights some future research directions, which need to be explored further to produce innovative technologies to control this pandemic.