Faculty Profiles

Dias, B. S. S., Querrer, R., Figueiredo, P. T., Leite, A. F., Melo, N. S. de, Costa, L. R., … Queiroz de Farias, M. C. (n.d.). Osteoporosis Screening: Leveraging EfficientNet with Complete and Cropped Facial Panoramic Radiography Imaging. Biomedical Signal Processing and Control, Volume 100, Part B. https://doi.org/10.1016/j.bspc.2024.107031

Zhang, Y., Chandler, D. M., & Queiroz de Farias, M. C. (2025). Motion deblurring via multiscale residual convolutional dictionary learning. Digital Signal Processing, 165. https://doi.org/https://doi.org/10.1016/j.dsp.2025.105337

Mithila, M. M. R., & Queiroz de Farias, M. C. (2025). MS-SCANET: A multiscale transformer-based architecture with dual attention for no-reference image quality assessment. https://doi.org/10.1109/ICASSP49660.2025.10887759

Lima, J. A., Miosso, C. J., & Farias, M. C. Q. (2025). SynFlowMap: A synchronized optical flow remapping for video motion magnification. Signal Processing: Image Communication, 117203. https://doi.org/10.1016/j.image.2024.117203

De Castro Araujo, G., Garcia, H. D., Queiroz de Farias, M. C., Prakash, R., & Menezes De Carvalho, M. (2025). A 360-degree Video Player for Dynamic Video Editing Applications. ACM Transactions on Multimedia Computing, Communications, and Applications. https://doi.org/10.1145/3715135

Alamgeer, S., Irshad, M., & Queiroz de Farias, M. C. (n.d.). Assessing the quality of light field images: A graph-based approach. Journal of Imaging Science and Technology, 69. https://doi.org/https://doi.org/10.1117/1.JEI.30.6.063001

Peixoto, E., Freitas, P. G., Queiroz de Farias, M. C., Medeiros, E., Guimarães, F., Dionísio, F., … Cosme, C. (2024). A Subjective Quality Evaluation Procedure for Bitrate Determination of TV 3.0 Videos. SET INTERNATIONAL JOURNAL OF BROADCAST ENGINEERING. https://doi.org/10.18580/setijbe.2024.1

Carvalho, A. H. S., Freitas, P. G., Gonçalves, M., Homonnai, J., & Queiroz de Farias, M. C. (2024). Perception-Driven Point Cloud Quality Assessment through Projections and Deep Structure Similarity. NYC, US: IEEE.

Yang, Q., Zhang, Y., Chandler, D., & Farias, M. C. Q. (2024). SSRT: Intra- and cross-view attention for stereo image super-resolution. Multimedia Tools and Applications. https://doi.org/10.1007/s11042-024-20000-9

Bauchspiess, R., & Farias, M. C. Q. (2024). A Degradation-Robust Deep Learning Framework for MRI Brain Tumor Diagnosis. In 2024 IEEE International Symposium on Biomedical Imaging (ISBI) (pp. 1--4). https://doi.org/10.1109/ISBI56570.2024.10635514

Zhao, S., Mahmoudpour, S., Farias, M. C. Q., Pagliari, C., & Schelkens, P. (2024). A Subjective Test Framework for JPEG Pleno Quality Assessment (pp. 92--95). IEEE. https://doi.org/10.1109/QoMEX61742.2024.10598240

Peixoto, E., Freitas, P., Farias, M. C. Q., Guimaraes De Medeiros, J. E., Guimaraes, F., Dionisio, F., … Cosme, C. (2024). Towards the Future of the Brazilian Digital Television Standard: Subjective Video Quality Evaluation for Next-Generation Broadcasting in Brazil (pp. 19--27). https://doi.org/10.1145/3672406.3672410

Althoff, L. S., Silva, A. R., Menezes De Carvalho, M., & Queiroz de Farias, M. C. (2024). 360Align: An Open Dataset and Software for Investigating QoE and Head Motion in 360° Videos with Alignment Edits. In The ACM International Conference on Interactive Media Experiences (IMX) (pp. 41–55). https://doi.org/https://doi.org/10.1145/3639701.3656311

Farias, M. C. Q. (2024). Quality of Experience of Virtual Reality-Based Communication Applications. In Electronic Imaging (Vol. 36, pp. 1--6). Society for Imaging Science and Technology. https://doi.org/10.2352/EI.2024.36.9.IQSP-267

Chetouani, A., Bosse, S., Le Callet, P., Queiroz de Farias, M. C., Ballé, J., & Li, J. (Eds.). (2024). Editorial Advancements in Learning-Based Quality Prediction for Advanced Visual Media. IEEE Journal of Selected Topics in Signal Processing (6th ed., Vol. 17). US: IEEE. https://doi.org/10.1109/JSTSP.2023.3337626

Queiroz de Farias, M. C. (2023). Quality of Experience of Immersive Media--New Challenges. https://doi.org/10.1145/3617023.3617025

Alamgeer, S., Costa, A. H. M., & Queiroz de Farias, M. C. (2023). Using a Diverse Neural Network to Predict the Quality of Light Field Images. IEEE. https://doi.org/10.1109/MMSP59012.2023.10337707

Correia, I. B. M. C., Queiroz de Farias, M. C., Hung, E., Guimarães, U. S., Vieira Jr, H., & Rodrigues, T. B. (2023). Estudo Comparativo da Detecção de Desmatamento em Cenas Sentinel-1 da Floresta Amazônica. https://doi.org/10.14209/sbrt.2023.1570923825

Althoff, L. S., Queiroz de Farias, M. C., Silva, A. R., & Menezes De Carvalho, M. (2023). Impact of Alignment Edits on the Quality of Experience of 360° Videos. IEEE Access, 11, 108475–108492. https://doi.org/10.1109/ACCESS.2023.3319346

Araújo, G. D., Garcia, H. D., Queiroz de Farias, M. C., Prakash, R., & Menezes De Carvalho, M. (2023). 360EAVP: A 360-degree Edition-Aware Video Player. In Proceedings of the 15th International Workshop on Immersive Mixed and Virtual Environment Systems. ACM. https://doi.org/10.1145/3592834.3592879

Freitas, P. G., Diniz, R., & Queiroz de Farias, M. C. (2023). Assessing the quality of 3D point clouds using descriptors for color and geometry texture. Brazilian Journal of Development, 9(5), 17415–17431. https://doi.org/https://doi.org/10.34117/bjdv9n5-196

Freitas, P. G., Diniz, R., & Queiroz de Farias, M. C. (2023). Point cloud quality assessment: unifying projection, geometry, and texture similarity. Visual Computer, 39(5), 1907–1914. https://doi.org/10.1007/s00371-022-02454-w

Alamgeer, S., & Queiroz de Farias, M. C. (2023). A two-stream CNN based visual quality assessment method for light field images. Multimedia Tools and Applications, 82, 5743–5762. https://doi.org/https://doi.org/10.1007/s11042-022-13436-4

Queiroz de Farias, M. C., Castro, P. H., Lopes, G., Miosso, C. J., & Lima, J. A. (2023). The Influence of Magnetic Resonance Imaging Artifacts on CNN-Based Brain Cancer Detection Algorithms. Computational Mathematics and Modeling, 33(2), 211–229. https://doi.org/10.1007/s10598-023-09567-4

Pchelintsev, Ya. A., Khvostikov, A. V., Krylov, A. A., Parolina, L. E., Nikoforova, N. A., Shepeleva, L. P., … Yong, D. (2023). Hardness Analysis of X-Ray Images for Neural-Network Tuberculosis Diagnosis. Computational Mathematics and Modeling, 33(2), 230–243. https://doi.org/10.1007/s10598-023-09568-3

Queiroz de Farias, M. C., Yong, D., & Krylov, A. S. (2023). On The Intelligent Medical Image Analysis and Processing. Computational Mathematics and Modeling, 33, 210. https://doi.org/10.1007/s10598-023-09566-5

Alamgeer, S., & Queiroz de Farias, M. C. (2023). A survey on visual quality assessment methods for light fields. Signal Processing: Image Communication, 110(January 2023). https://doi.org/https://doi.org/10.1016/j.image.2022.116873

Prado, M., Althoff, L., Alamgeer, S., Silva, A. R. e, Prakash, R., Menezes De Carvalho, M., & Queiroz de Farias, M. C. (2022). 360RAT: A Tool for Annotating Regions of Interest in 360-Degree Videos. In Proceedings of the Brazilian Symposium on Multimedia and the Web (pp. 272–280). New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3539637.3557930

Althoff, L. dos S., Garcia, H. D., Morais, D. D. R., Alamgeer, S., Prado, M. A., Araujo, G. C., … Queiroz de Farias, M. C. (2022). Designing an user-centric framework for perceptually-efficient streaming of 360-degree edited videos. In Electronic Imaging (9th ed., Vol. 34, pp. 394–1--394–1). https://doi.org/10.2352/EI.2022.34.9.IQSP-394

Saigg, C. L., Dias, B. S., Costa, A. H., Queiroz de Farias, M. C., & Martinez, H. B. (2022). A Python Framework for Objective Visual Quality Assessment. In Anais Estendidos do XXXV Conference on Graphics, Patterns and Images (pp. 105--109). https://doi.org/https://doi.org/10.5753/sibgrapi.est.2022.23271

Weigang, L., Martins, L., Ferreira, N., Miranda, C., Althoff, L., Pessoa, W., … Rincon, M. (2022). Heuristic Once Learning for Image & Text Duality Information Processing (pp. 1353--1359). https://doi.org/10.1109/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00195

Althoff, L., Queiroz de Farias, M. C., & Weigang, L. (2022). Once Learning for Looking and Identifying Based on YOLO-v5 Object Detection (pp. 298--304). https://doi.org/https://doi.org/10.1145/3539637.3557929

Alamgeer, S., & Queiroz de Farias, M. C. (2022). Light Field Image Quality Assessment with Dense Atrous Convolutions. Brasília, Brazil. https://doi.org/10.1109/ICIP46576.2022.9897598

Freitas, P. G., Lucafo, G. D., Gonçalves, M., Homonnai, J., Diniz, R., & Queiroz de Farias, M. C. (2022). Comparative Evaluation of Temporal Pooling Methods for No-Reference Quality Assessment of Dynamic Point Clouds (pp. 35–41). ACM. https://doi.org/10.1145/3552482.3556552

Alamgeer, S., & Queiroz de Farias, M. C. (2022). Deep Learning-Based Light Field Image Quality Assessment Using Frequency Domain Inputs. https://doi.org/10.1109/QoMEX55416.2022.9900901

Martinez, H., Hines, A., & Queiroz de Farias, M. C. (2022). See hear now: is audio-visual QoE now just a fusion of audio and video metrics? https://doi.org/10.1109/QoMEX55416.2022.9900891

Oliveira, P. H., Ferreira, D. S., Krylov, A. A., Ding, Y., & Queiroz de Farias, M. C. (2022). Using a Saliency-Driven Convolutional Neural Network Framework for Brain Tumor Detection. https://doi.org/10.1145/3545729.3545762

Freitas, P. G., Gonçalves, M., Homonnai, J., Diniz, R., & Queiroz de Farias, M. C. (2022). On the Performance of Temporal Pooling Methods for Quality Assessment of Dynamic Point Clouds. IEEE. https://doi.org/10.1109/QoMEX55416.2022.9900906

Alamgeer, S., & Queiroz de Farias, M. C. (2022). No-Reference Light Field Image Quality Assessment Method Based on a Long-Short Term Memory Neural Network. IEEE. https://doi.org/10.1109/ICMEW56448.2022.9859419

Alamgeer, S., & Queiroz de Farias, M. C. (2022). Blind visual quality assessment of light field images based on distortion maps. Frontiers in Signal Processing, 2. https://doi.org/doi: 10.3389/frsip.2022.815058

Thomaz, A., Lima, J. A., Miosso, C., Queiroz de Farias, M. C., Krylov, A., & Ding, Y. (2022). Undersampled Magnetic Resonance Image Reconstructions Based on a Combination of U-Nets and L1, L2, and TV Optimizations. IEEE. https://doi.org/10.1109/IST55454.2022.9827727

Dovganich, A. A., Khvostikov, A. V., Pchelintsev, Y. A., Krylov, A. A., Ding, Y., & Queiroz de Farias, M. C. (2022). Automatic Out-of-Distribution Detection Methods for Improving the Deep Learning Classification of Pulmonary X-ray Images. Journal of Image and Graphics, 10(2), 56–63. https://doi.org/10.18178/joig.10.2.56-63

Diniz, R., Garcia Freitas, P., & Queiroz de Farias, M. C. (2022). Point cloud quality assessment based on geometry-aware texture descriptors. Computers & Graphics, 103, 31–44. https://doi.org/10.1016/j.cag.2022.01.003

Dowsley, R., Queiroz de Farias, M. C., Larangeira, M., Nascimento, A., & Virdee, J. (2022). A Spendable Cold Wallet from QR Video (pp. 283–290). Scitepress. https://doi.org/10.5220/0011138300003283

Morais, D. D. R., Althoff, L. S., Prakash, R., Menezes De Carvalho, M., & Queiroz de Farias, M. C. (2021). A content-based viewport prediction model. In IS&T International Symposium on Electronic Imaging Science and Technology. https://doi.org/10.2352/ISSN.2470-1173.2021.9.IQSP-255

Ansari, G. J., Shah, J. H., Queiroz de Farias, M. C., Sharif, M., Qadeer, N., & Khan, H. U. (2021). An Optimized Feature Selection Technique in Diversified Natural Scene Text for Classification Using Genetic Algorithm. IEEE Access, 9, 54923–54937. https://doi.org/10.1109/access.2021.3071169

Diniz, R., Garcia Freitas, P., & Queiroz de Farias, M. C. (2021). Color and Geometry Texture Descriptors for Point-Cloud Quality Assessment. IEEE Signal Processing Letters, 28, 1150–1154. https://doi.org/10.1109/lsp.2021.3088059

Becerra Martinez, H., Hines, A., & Queiroz de Farias, M. C. (2021). Perceptual Quality of Audio-Visual Content with Common Video and Audio Degradations. Applied Sciences, 11(13), 5813. https://doi.org/10.3390/app11135813

Diniz, R., Freitas, P. G., & Queiroz de Farias, M. C. (2021). A novel point cloud quality assessment metric based on perceptual color distance patterns. https://doi.org/10.2352/ISSN.2470-1173.2021.9.IQSP-256

Martinez, H. B., Costa, A. H., Azambuja, B., Hines, A., & Queiroz de Farias, M. C. (2021). Exploring the boundaries of an AE-based quality model: A performance analysis via synthetic content. https://doi.org/10.2352/ISSN.2470-1173.2021.9.IQSP-266

Alamgeer, S., & Queiroz de Farias, M. C. (2021). CNN-based no-reference video quality assessment method using a spatiotemporal saliency patch selection procedure. Journal of Electronic Imaging. https://doi.org/10.1117/1.JEI.30.6.063001

Costa, A. H., Martinez, H. B., Silva, D. G., & Queiroz de Farias, M. C. (2021). Analyzing the effect of adding temporal features to an autoencoder-based video quality model. https://doi.org/10.2352/ISSN.2470-1173.2021.9.IQSP-261

Garcia, H. D., Queiroz de Farias, M. C., Prakash, R., & Menezes De Carvalho, M. (2020). Statistical characterization of tile decoding time of HEVC-encoded 360° video. In IS&T International Symposium on Electronic Imaging Science and Technology. https://doi.org/10.2352/ISSN.2470-1173.2020.9.IQSP-285

Min, X., Zhai, G., Zhou, J., Queiroz de Farias, M. C., & Bovik, A. C. (2020). Study of Subjective and Objective Quality Assessment of Audio-Visual Signals. IEEE Transactions on Image Processing, 29, 6054–6068. https://doi.org/10.1109/tip.2020.2988148

Martinez, H. B., Hines, A., & Queiroz de Farias, M. C. (2020). UnB-AV: An Audio-Visual Database for Multimedia Quality Research. IEEE Access, 8, 56641–56649. https://doi.org/10.1109/access.2020.2981861

Diniz, R., Freitas, P. G., & Queiroz de Farias, M. C. (2020). Multi-Distance Point Cloud Quality Assessment. In International Conference on Image Processing, ICIP. https://doi.org/10.1109/ICIP40778.2020.9190956

Nunes, G., Oliveira, F., Queiroz de Farias, M. C., Gomes, J. G. R., Petraglia, A., Fernandez-Berni, J., … Rodriguez-Vazquez, A. (2020). Comparison between Digital Tone-Mapping Operators and a Focal-Plane Pixel-Parallel Circuit. Signal Processing: Image Communication. https://doi.org/10.1016/j.image.2020.115937

Freitas, P. G., Eira, L. P., Santos, S. S., & Queiroz de Farias, M. C. (2020). Image quality assessment using BSIF, CLBP, LCP, and LPQ operators. Theoretical Computer Science, 805, 37–61. https://doi.org/10.1016/j.tcs.2019.10.038

Lima, J. A., Silva, F. B., von Borries, R., Miosso, C. J., & Queiroz de Farias, M. C. (2020). Isotropic and anisotropic filtering norm-minimization: A generalization of the TV and TGV minimizations using NESTA. Signal Processing: Image Communication. https://doi.org/10.1016/j.image.2020.115856

Diniz, R., Freitas, P. G., & Queiroz de Farias, M. C. (2020). Local luminance patterns for point cloud quality assessment. https://doi.org/10.1109/MMSP48831.2020.9287154

Lima, J. A., Miosso, C. J., & Queiroz de Farias, M. C. (2020). Hybrid Motion Magnification based on Same-Frame Optical Flow Computations. https://doi.org/10.1109/MMSP48831.2020.9287152

Silva, A. R., & Queiroz de Farias, M. C. (2020). Perceptual quality assessment of 3D videos with stereoscopic degradations. Multimedia Tools and Applications, 79, 1603–1623. https://doi.org/10.1007/s11042-019-08386-3

Martinez, H. B., Hines, A., & Queiroz de Farias, M. C. (2020). HOW DEEP IS YOUR ENCODER: AN ANALYSIS OF FEATURES DESCRIPTORS FOR AN AUTOENCODER-BASED AUDIO-VISUAL QUALITY METRIC. In arXiv. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-85094392215&partnerID=MN8TOARS

Diniz, R., Freitas, P. G., & Queiroz de Farias, M. C. (2020). Towards a point cloud quality assessment model using local binary patterns. IEEE. https://doi.org/10.1109/QoMEX48832.2020.9123076

Nasrabadi, A. T., Samiei, A., Mahzari, A., McMahan, R. P., Prakash, R., Queiroz de Farias, M. C., & Menezes De Carvalho, M. (2019). A taxonomy and dataset for 360°videos. In Proc. of the 10th ACM Multimedia Systems Conference (MMSys). https://doi.org/10.1145/3304109.3325812

Martinez, H. B., Queiroz de Farias, M. C., & Hines, A. (2019). Navidad: A no-reference audio-visual quality metric based on a deep autoencoder. In European Signal Processing Conference. https://doi.org/10.23919/EUSIPCO.2019.8902975

Melgar, M. V., & Queiroz de Farias, M. C. (2019). A (2,2) XOR-based visual cryptography scheme without pixel expansion. Journal of Visual Communication and Image Representation, 63. https://doi.org/10.1016/j.jvcir.2019.102592

Sanchez-Ferreira, C., Coelho, L., Ayala, H., Queiroz de Farias, M. C., & Llanos, C. H. (2019). Bio-inspired optimization algorithms for real underwater image restoration. Signal Processing: Image Communication, 77, 49–65. https://doi.org/10.1016/j.image.2019.05.015

Melgar, M. V., & Queiroz de Farias, M. C. (2019). High density two-dimensional color code. Multimedia Tools and Applications, 78, 1949–1970. https://doi.org/10.1007/s11042-018-6299-4

Martinez, H. B., Queiroz de Farias, M. C., & Hines, A. (2019). A No-Reference Autoencoder Video Quality Metric. https://doi.org/10.1109/ICIP.2019.8803204

Akamine, W. Y. L., Freitas, P. G., & Queiroz de Farias, M. C. (2019). A framework for computationally efficient video quality assessment. Signal Processing: Image Communication, 70, 57–67. https://doi.org/10.1016/j.image.2018.09.009

Garcia Freitas, P., da Eira, L., Santos, S., & Queiroz de Farias, M. C. (2018). On the Application LBP Texture Descriptors and Its Variants for No-Reference Image Quality Assessment. Journal of Imaging, 4(10), 114. https://doi.org/10.3390/jimaging4100114

Freitas, P. G., Akamine, W., & Queiroz de Farias, M. C. (2018). No-reference image quality assessment using salient local binary patterns. In IS and T International Symposium on Electronic Imaging Science and Technology. https://doi.org/10.2352/ISSN.2470-1173.2018.12.IQSP-367

da Silva, A. F., & Queiroz de Farias, M. C. (2018). Perceptual strengths of video impairments that combine blockiness, blurriness, and packet-loss artifacts. In IS and T International Symposium on Electronic Imaging Science and Technology. https://doi.org/10.2352/ISSN.2470-1173.2018.12.IQSP-234

Freitas, P. G., Akamine, W., & Queiroz de Farias, M. C. (2018). Referenceless image quality assessment by saliency, color-texture energy, and gradient boosting machines. Journal of the Brazilian Computer Society. https://doi.org/10.1186/s13173-018-0073-3

Martinez, H. B., & Queiroz de Farias, M. C. (2018). Combining audio and video metrics to assess audio-visual quality. Multimedia Tools and Applications, 77, 23993--24012. https://doi.org/10.1007/s11042-018-5656-7

Freitas, P. G., Silva, A. F., Redi, J., & Queiroz de Farias, M. C. (2018). Performance analysis of a video quality ruler methodology for subjective quality assessment. Journal of Electronic Imaging, 27, 053020--053020. https://doi.org/10.1117/1.JEI.27.5.053020

Silva, A. F., & Queiroz de Farias, M. C. (2018). Using perceptual strength estimates to predict the perceived annoyance of videos with combinations of spatial and temporal artifacts. Journal of Electronic Imaging, 27, 043018--043018. https://doi.org/10.1117/1.JEI.27.4.043018

Freitas, P. G., Alamgeer, S., Akamine, W., & Queiroz de Farias, M. C. (2018). Blind image quality assessment based on multiscale salient local binary patterns. ACM. https://doi.org/10.1145/3204949.3204960

Freitas, P. G., Akamine, W. Y., & Queiroz de Farias, M. C. (2018). Using multiple spatio-temporal features to estimate video quality. Signal Processing: Image Communication, 64. https://doi.org/10.1016/j.image.2018.02.010

Freitas, P. G., Akamine, W. Y., & Queiroz de Farias, M. C. (2018). No-Reference Image Quality Assessment Using Orthogonal Color Planes Patterns. IEEE Transactions on Multimedia, 20(12), 3353–3360. https://doi.org/10.1109/tmm.2018.2839529

Freitas, P. G., Akamine, W., & Queiroz de Farias, M. C. (2017). Blind image quality assessment using multiscale local binary patterns. https://doi.org/10.2352/ISSN.2470-1173.2017.12.IQSP-A

Lima, J. A., Queiroz de Farias, M. C., & Miosso, C. J. (2017). Per-pixel mirror-based method for high-speed video acquisition. Journal of Visual Communication and Image Representation, 47. https://doi.org/10.1016/j.jvcir.2017.05.004

Silva, A. F., Queiroz de Farias, M. C., & Redi, J. (2016). Annoyance models for videos with spatio-temporal artifacts. In 2016 8th International Conference on Quality of Multimedia Experience, QoMEX 2016. https://doi.org/10.1109/QoMEX.2016.7498971

Akamine, W., Freitas, P. G., & Queiroz de Farias, M. C. (2016). No-reference image quality assessment based on statistics of Local Ternary Pattern. In 2016 8th International Conference on Quality of Multimedia Experience, QoMEX 2016. https://doi.org/10.1109/QoMEX.2016.7498959

Sanchez-Ferreira, C., Mori, J., Queiroz de Farias, M. C., & Llanos, C. (2016). A real-time stereo vision system for distance measurement and underwater image restoration. Journal of the Brazilian Society of Mechanical Sciences and Engineering. https://doi.org/10.1007/s40430-016-0596-5

Rigoni, R., Freitas, P. G., & Queiroz de Farias, M. C. (2016). Detecting tampering in audio-visual content using QIM watermarking. Information Sciences. https://doi.org/10.1016/j.ins.2015.08.040

Freitas, P., Queiroz de Farias, M. C., & Araujo, A. (2016). Enhancing inverse halftoning via coupled dictionary training. Signal Processing: Image Communication, 49. https://doi.org/10.1016/j.image.2016.09.008

Freitas, P. G., Queiroz de Farias, M. C., & Araujo, A. (2016). Hiding color watermarks in halftone images using maximum-similarity binary patterns. Signal Processing: Image Communication, 48. https://doi.org/10.1016/j.image.2016.08.007

Silva, A. F., Queiroz de Farias, M. C., & Redi, J. (2016). Perceptual Annoyance Models for Videos with Combinations of Spatial and Temporal Artifacts. IEEE Transactions on Multimedia, 18, 2446--2456. https://doi.org/10.1109/TMM.2016.2601027

Freitas, P. G., Rigoni, R., & Queiroz de Farias, M. C. (2016). Secure self-recovery watermarking scheme for error concealment and tampering detection. Journal of the Brazilian Computer Society, 22(1). https://doi.org/10.1186/s13173-016-0046-3

Leszczuk, M., Hanusiak, M., Queiroz de Farias, M. C., Wyckens, E., & Heston, G. (2016). Recent developments in visual quality monitoring by key performance indicators. Multimedia Tools and Applications, 75(17), 10745–10767. https://doi.org/10.1007/s11042-014-2229-2

Dias, E., Vargas, E. E., Queiroz de Farias, M. C., & Menezes De Carvalho, M. (2015). Feasibility of video streaming offloading via connection sharing from LTE to WiFi ad hoc networks. In International Workshop on Telecommunications (IWT). https://doi.org/10.1109/IWT.2015.7224552

Freitas, P., Queiroz de Farias, M. C., & Araujo, A. (2015). Improved performance of inverse halftoning algorithms via coupled dictionaries. IEEE. https://doi.org/10.1109/ICME.2015.7177457

Freitas, P. G., Redi, J., & Queiroz de Farias, M. C. (2015). Video quality ruler: A new experimental methodology for assessing video quality. In 2015 7th International Workshop on Quality of Multimedia Experience, QoMEX 2015. https://doi.org/10.1109/QoMEX.2015.7148137

Vizcarra Melgar, M. E., Queiroz de Farias, M. C., & Zaghetto, A. (2015). An evaluation of the effect of JPEG, JPEG2000, and H.264/AVC on CQR codes decoding process. In N. Sampat, R. Tezaur, & D. Wüller (Eds.), Digital Photography XI. SPIE. https://doi.org/10.1117/12.2083263

Martinez, H. B., & Queiroz de Farias, M. C. (2014). Full-reference audio-visual video quality metric. Journal of Electronic Imaging. https://doi.org/10.1117/1.jei.23.6.061108

Akamine, W. Y., & Queiroz de Farias, M. C. (2014). Video quality assessment using visual attention computational models. Journal of Electronic Imaging, 23(6), 061107. https://doi.org/10.1117/1.jei.23.6.061107

Freitas, P. G., Queiroz de Farias, M. C., & De Araujo, A. P. (2014). A Parallel Framework for Video Super-Resolution. In 2014 27th SIBGRAPI Conference on Graphics, Patterns and Images. IEEE. https://doi.org/10.1109/sibgrapi.2014.15

Rigoni, R., Freitas, P. G., & Queiroz de Farias, M. C. (2014). Tampering Detection of Audio-Visual Content Using Encrypted Watermarks. In 2014 27th SIBGRAPI Conference on Graphics, Patterns and Images. IEEE. https://doi.org/10.1109/sibgrapi.2014.50

Redi, J., Heynderickx, I., Macchiavello, B., & Queiroz de Farias, M. C. (2013). On the impact of packet-loss impairments on visual attention mechanisms. In IEEE International Symposium on Circuits and Systems. https://doi.org/10.1109/ISCAS.2013.6572044

Queiroz de Farias, M. C., & Mitra, S. K. (2012). Perceptual contributions of blocky, blurry, noisy, and ringing synthetic artifacts to overall annoyance. Journal of Electronic Imaging, 21(4), 043013. https://doi.org/10.1117/1.jei.21.4.043013

Queiroz de Farias, M. C., & Akamine, W. (2012). On performance of image quality metrics enhanced with visual attention computational models. Electronics Letters. https://doi.org/10.1049/el.2012.0642

Freitas, P. G., Rigoni, R., Queiroz de Farias, M. C., & Araujo, A. P. F. (2012). Error Concealment Using a Halftone Watermarking Technique. In 2012 25th SIBGRAPI Conference on Graphics, Patterns and Images. IEEE. https://doi.org/10.1109/sibgrapi.2012.50

Queiroz de Farias, M. C., Menezes De Carvalho, M., Kussaba, H. T., & Noronha, B. H. (2011). A hybrid metric for digital video quality assessment. In IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB). https://doi.org/10.1109/BMSB.2011.5954900

Queiroz de Farias, M. C. (2011). Visual-quality estimation using objective metrics. Journal of the Society for Information Display. https://doi.org/10.1889/JSID19.11.764

Freitas, P., Queiroz de Farias, M. C., & Araujo, A. (2011). Fast Inverse Halftoning Algorithm for Ordered Dithered Images. In 2011 24th SIBGRAPI Conference on Graphics, Patterns and Images. IEEE. https://doi.org/10.1109/sibgrapi.2011.14

Queiroz de Farias, M. C., & Menezes De Carvalho, M. (2010). Video quality assessment based on data hiding for IEEE 802.11 wireless networks. In IEEE International Symposium on Broadband Multimedia Systems and Broadcasting 2010, BMSB 2010 - Final Programme. https://doi.org/10.1109/ISBMSB.2010.5463168

Regis, C. D., Morais, D. C., Alencar, M. S., & Queiroz de Farias, M. C. (2009). Objective and subjective assessment of space-transcoded videos for mobile receivers. In 2009 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting. IEEE. https://doi.org/10.1109/isbmsb.2009.5133796

Queiroz de Farias, M. C., Menezes De Carvalho, M., & Alencar, M. S. (2008). Digital television broadcasting in Brazil. IEEE Multimedia. https://doi.org/10.1109/MMUL.2008.25

Queiroz de Farias, M. C. (2008). No-Reference and Reduced Reference Video Quality Metrics. VDM Verlag. Germany.

Foley, J. M., Varadharajan, S., Koh, C., & Queiroz de Farias, M. C. (2007). Detection of Gabor patterns of different sizes, shapes, phases and eccentricities. Vision Research, 47, 85–107. https://doi.org/10.1016/j.visres.2006.09.005

Queiroz de Farias, M. C., Foley, J. M., & Mitra, S. K. (2007). Detectability and annoyance of synthetic blocky, blurry, noisy, and ringing artifacts. IEEE Transactions on Signal Processing, 55, 2954--2964. https://doi.org/10.1109/TSP.2007.893963

Queiroz de Farias, M. C., & Mitra, S. K. (2005). No-reference video quality metric based on artifact measurements (Vol. 3, p. III--141). IEEE. https://doi.org/10.1109/ICIP.2005.1530348

Chowdary, A. B., Queiroz de Farias, M. C., Mitra, S. K., & Marco, M. (2005). A robust error concealment technique using data hiding for image and video transmission over lossy channels. IEEE Transactions on Circuits and Systems for Video Technology, 15(11), 1394--1406. https://doi.org/10.1109/TCSVT.2005.856933

Queiroz de Farias, M. C., Carli, M., & Mitra, S. (2005). Objective video quality metric based on data hiding. IEEE Transactions on Consumer Electronics, 51(3), 983--992. https://doi.org/10.1109/TCE.2005.1510512

Queiroz de Farias, M. C., Foley, J. M., & Mitra, S. K. (2005). Detectability and annoyance of synthetic blockiness, blurriness, noisiness, and ringing in video sequences. https://doi.org/10.1109/ICASSP.2005.1415464

Queiroz de Farias, M. C., Foley, J. M., & Mitra, S. K. (2005). Perceptual analysis of video impairments that combine blocky, blurry, noisy, and ringing synthetic artifacts. In Proceedings of SPIE - The International Society for Optical Engineering. https://doi.org/10.1117/12.587372

Carli, M., Queiroz de Farias, M. C., Gelasca, E., Tedesco, R., & Neri, A. (2005). Quality assessment using data hiding on perceptually important areas. In Proceedings - International Conference on Image Processing, ICIP. https://doi.org/10.1109/ICIP.2005.1530613

Gelasca, E., Queiroz de Farias, M. C., Ebrahimi, T., Carli, M., & Mitra, S. K. (2004). Towards perceptually driven segmentation evaluation metrics. IEEE. https://doi.org/10.1109/CVPR.2004.465

Queiroz de Farias, M. C., Moore, M. S., Foley, J. M., & Mitra, S. K. (2004). Perceptual contributions of blocky, blurry, and fuzzy impairments to overall annoyance. Proceedings of SPIE - The International Society for Optical Engineering. https://doi.org/10.1117/12.527222

Queiroz de Farias, M. C., Carli, M., Neri, A., & Mitra, S. K. (2004). Video quality assessment based on data hiding driven by optical flow information. In Proceedings of SPIE - The International Society for Optical Engineering. https://doi.org/10.1117/12.527792

Gelasca, E., Queiroz de Farias, M. C., Ebrahimi, T., Carli, M., & Mitra, S. K. (2004). Annoyance of spatio-temporal artifacts in segmentation quality assessment. https://doi.org/10.1109/ICIP.2004.1418761

Queiroz de Farias, M. C., Mitra, S. K., & Foley, J. M. (2004). Detectability and annoyance of synthetic blurring and ringing in video sequences. In Proceedings. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-4544380362&partnerID=MN8TOARS

Gelasca, E., Ebrahimi, T., Queiroz de Farias, M. C., & Mitra, S. K. (2004). Impact of topology changes in video segmentation evaluation. IEEE.

Queiroz de Farias, M. C., Foley, J. M., & Mitra, S. K. (2003). Perceptual contributions of blocky, blurry and noisy artifacts to overall annoyance. https://doi.org/10.1109/ICME.2003.1220971

Queiroz de Farias, M. C., Foley, J. M., & Mitra, S. K. (2003). Some Properties of Synthetic Blocky and Blurry Artifacts. In Proceedings of SPIE - The International Society for Optical Engineering. https://doi.org/10.1117/12.477381

Adsumilli, C., Queiroz de Farias, M. C., Carli, M., & Mitra, S. (2003). A hybrid constrained unequal error protection and data hiding scheme for packet video transmission. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-0141743443&partnerID=MN8TOARS

Gomes, J. G. R., Queiroz de Farias, M. C., Mitra, S., & Carli, M. (2003). An accurate billing mechanism for multimedia communications.

Queiroz de Farias, M. C., Mitra, S., Carli, M., & Neri, A. (2002). A comparison between an objective quality measure and the mean annoyance values of watermarked videos. In IEEE International Conference on Image Processing -ICIP. US: IEEE. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-0036452089&partnerID=MN8TOARS

Carli, M., Bailey, D., Queiroz de Farias, M. C., & Mitra, S. K. (2002). Error control and concealment for video transmission using data hiding. In International Symposium on Wireless Personal Multimedia Communications, WPMC. https://doi.org/10.1109/WPMC.2002.1088289

Queiroz de Farias, M. C., Carli, M., Foley, J. M., & Mitra, S. K. (2002). Detectability and annoyance of artifacts in watermarked digital videos. In European Signal Processing Conference. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-84960841832&partnerID=MN8TOARS

Queiroz de Farias, M. C., Moore, M. S., Foley, J. M., & Mitra, S. K. (2002). Detectability and annoyance of synthetic blocky and blurry video artifacts (Vol. 33, pp. 708–711). SID.

Bailey, D., Carli, M., Queiroz de Farias, M. C., & Mitra, S. K. (2002). Quality assessment for block-based compressed images and videos with regard to blockiness artifacts (Vol. 9).

Queiroz de Farias, M. C., Mitra, S. K., & Carli, M. (2002). Video quality objective metric using data hiding. In Proceedings of 2002 IEEE Workshop on Multimedia Signal Processing, MMSP 2002. https://doi.org/10.1109/MMSP.2002.1203346