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    A bit rate adaptation model for 3D video
    (Springer, 2016) Yilmaz, Gokce Nur
    Although a significant research effort has been carried out for investigating 3 Dimensional (3D) video display, transmission, coding, etc, the same is not applicable for 3D video adaptation. In addition, ambient illumination, spatial resolution and 3D video content related contexts have not been particularly considered in a hybrid manner for the 3D video adaptation purpose in literature to date. In this paper, an adaptation decision taking technique is designed to predict the bit rate of 3D video sequences to be adapted by a proposed adaptation model. The ambient illumination condition of the viewing environment is considered in these proposed technique and model together with spatial resolution, video quality, and depth perception related contexts of the 3D video. Experimental results derived by the assistance of subjective experiments prove that the proposed model is quite efficient to adapt the 3D video sequences without compromising the 3D video perception of the users.
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    Blind video quality assessment via spatiotemporal statistical analysis of adaptive cube size 3D-DCT coefficients
    (INST ENGINEERING TECHNOLOGY-IET, 2020) Cemiloglu, Enes; Yilmaz, Gokce Nur
    There is an urgent need for a robust video quality assessment (VQA) model that can efficiently evaluate the quality of a video content varying in terms of the distortion and content type in the absence of the reference video. Considering this need, a novel no reference (NR) model relying on the spatiotemporal statistics of the distorted video in a three-dimensional (3D)-discrete cosine transform (DCT) domain is proposed in this study. While developing the model, as the first contribution, the video contents are adaptively segmented into the cubes of different sizes and spatiotemporal contents in line with the human visual system (HVS) properties. Then, the 3D-DCT is applied to these cubes. Following that, as the second contribution, different efficient features (i.e. spectral behaviour, energy variation, distances between spatiotemporal frequency bands, and DC variation) associated with the contents of these cubes are extracted. After that, these features are associated with the subjective experimental results obtained from the EPFL-PoliMi video database using the linear regression analysis for building the model. The evaluation results present that the proposed model, unlike many top-performing NR-VQA models (e.g. V-BLIINDS, VIIDEO, and SSEQ), achieves high and stable performance across the videos with different contents and distortions.
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    A Comparative Study on No-Reference Video Quality Assessment Metrics
    (Ieee, 2014) Zerman, Emin; Akar, Gozde Bozdagi; Konuk, Baris; Yilmaz, Gokce Nur
    In the last two decades the Internet technology has boosted and the connection speeds have been incrased from kilobits to hundred megabits scale. With the rising coverage of the Internet and the usage of mobile devices such as tablets and smart phones, the usage of social media and especially multimedia elements has been increased rapidly. This increment in streaming multimedia created a need for the assessment of the user experience on multimedia and especially video. Even though there are different Video Quality Assessment (VQA) methods for that purpose, most of them are Full-Reference (FR) or Reduced-Reference (RR). In today's world with many mobile devices, the application of these methods are not possible since they need the reference data. The No-Reference (NR) video metrics are much more suitable for the case. In this paper, the main objective is to evaluate a previously proposed NR VQA metric with a new dataset and to compare the results to other high-performance NR metrics such as G.1070 and G.1070E which do not utilize spatial and temporal characteristics of a given video sequence. Evaluation and comparison results show the accuracy and robustness of the proposed metric.
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    A depth perception evaluation metric for immersive user experience towards 3D multimedia services
    (Springer, 2019) Bayrak, Huseyin; Yilmaz, Gokce Nur
    The interest of users towards three-dimensional (3D) video is gaining momentum due to the recent breakthroughs in 3D video entertainment, education, network, etc. technologies. In order to speed up the advancement of these technologies, monitoring quality of experience of the 3D video, which focuses on end user's point of view rather than service-oriented provisions, becomes a central concept among the researchers. Thanks to the stereoscopic viewing ability of human visual system (HVS), the depth perception evaluation of the 3D video can be considered as one of the most critical parts of this central concept. Due to the lack of efficiently and widely utilized objective metrics in literature, the depth perception assessment can currently only be ensured by cost and time-wise troublesome subjective measurements. Therefore, a no-reference objective metric, which is highly effective especially for on the fly depth perception assessment, is developed in this paper. Three proposed algorithms (i.e., Z direction motion, structural average depth and depth deviation) significant for the HVS to perceive the depth of the 3D video are integrated together while developing the proposed metric. Considering the outcomes of the proposed metric, it can be clearly stated that the provision of better 3D video experience to the end users can be accelerated in a timely fashion for the Future Internet multimedia services.
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    A novel depth perception prediction metric for advanced multimedia applications
    (Springer, 2019) Yilmaz, Gokce Nur
    Ubiquitous multimedia applications diffuse our everyday life activities which appreciate their significance about improving our experiences. Therefore, proliferation of the multimedia applications enhancing these experiences needs critical attention of the researchers. Considering this motivation, to overcome the possible barrier of the proliferation of the 3D video-related multimedia applications providing enhanced quality of experience (QoE) to the end users, an objective metric is proposed in this study. The proposed metric tackles the depth perception prediction part reflecting the most important aspect of the 3D video QoE from the user point of view. Considering that the no reference metric type is the most effective one compared to its counterparts, the proposed metric is developed based on this type. In the light of the envision that human visual system-related cues have critical importance on developing accurate metrics, the focus of the proposed metric is directed on the association of the z-direction motion and stereopsis depth cues in the metric development. These cues are derived from the depth map contents having stressed significant depth levels. In addition, the analysis results of the conducted subjective experiments which are currently the "gold standards" for the reliable depth perception prediction are incorporated with the proposed metric. Considering the effective correlation coefficient and root mean square error performance assessment results taken using the proposed metric in comparison to the widely exploited quality assessment metrics in literature, it can be clearly stated that the development of the improved 3D video multimedia applications can be accelerated using it.
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    Structural Depth Estimation Via Depth Maps Of 3 Dimensional Videos
    (Ieee, 2016) Bayrak, Huseyin; Yilmaz, Gokce Nur
    3-Dimensional (3D) Video Quality Assessment (VQA) has been an important area for researchers working in this area. The reason is there isn't any well accepted and standardized VQA method for 3 Dimensional (3D) as for 2-Dimensional (2D) video. Depth perception assessment (DPE) is the most critical part of 3D VQA because of visual realism. Subjective tests are currently in use for the 3D VQA because there aren't any 3D VQA algorithms for measuring this perception accepted by researchers in literature. Subjective tests are not ergonomic methods from the stand point of time and cost. Therefore, it is quite important to develop objective 3D VQA metrics for predicting the depth perception of users. The VQA algorithms developed without using a reference video is called No-Reference (NR) metrics in literature and they are considered efficient compared to the other metrics. In this study, Depth Maps (DM) in 2D+depth based 3D videos are utilized to measure Structural Average Depth (SAD) in a NR manner. The results of this study presents that the YOD algorithm can be considered as a part of a 3D VQA metric assessing the depth perception and approved by researchers.
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    Z-Direction Motion Estimation In 2d+Depth Map Based 3d Video
    (Ieee, 2014) Bayrak, Huseyin; Yilmaz, Gokce Nur; Tuna, Eyup
    3-Dimensional (3D) Video Quality Assessment (VQA) has been an important area for today's researchers along with the growing interest in 3D video. Even though, 2-Dimensional (2D) objective VQA metrics that are widely utilized by researchers in literature, the case is not the same for the 3D video. Therefore, subjective tests, which are inefficient in terms of time and cost are used for the 3D VQA. The VQA metrics are divided into three categories according to the use of the reference signal in the assessment as Full-Reference (FR), Reduced-Reference (RR) or No-Reference (NR). The NR metrics are more efficient compared to the other metrics. In this study, an algorithm that estimates the backward-forward z direction motion of the depth maps in 2D+depth map based 3D videos is proposed. The results indicate that the proposed algorithm is efficient to develop a NR VQA metric in future.