Paper Reading AI Learner

Toward Multimodal Interaction in Scalable Visual Digital Evidence Visualization Using Computer Vision Techniques and ISS

2018-08-01 00:28:32
Serguei A. Mokhov, Miao Song, Jashanjot Singh, Joey Paquet, Mourad Debbabi, Sudhir Mudur

Abstract

Visualization requirements in Forensic Lucid have to do with different levels of case knowledge abstraction, representation, aggregation, as well as the operational aspects as the final long-term goal of this proposal. It encompasses anything from the finer detailed representation of hierarchical contexts to Forensic Lucid programs, to the documented evidence and its management, its linkage to programs, to evaluation, and to the management of GIPSY software networks. This includes an ability to arbitrarily switch between those views combined with usable multimodal interaction. The purpose is to determine how the findings can be applied to Forensic Lucid and investigation case management. It is also natural to want a convenient and usable evidence visualization, its semantic linkage and the reasoning machinery for it. Thus, we propose a scalable management, visualization, and evaluation of digital evidence using the modified interactive 3D documentary system - Illimitable Space System - (ISS) to represent, semantically link, and provide a usable interface to digital investigators that is navigable via different multimodal interaction techniques using Computer Vision techniques including gestures, as well as eye-gaze and audio.

Abstract (translated)

Forensic Lucid中的可视化要求与不同级别的案例知识抽象,表示,聚合以及操作方面有关,作为该提案的最终长期目标。它包括从分层上下文到法医清醒程序的更精细的详细表示,到文档证据及其管理,与程序的链接,评估以及GIPSY软件网络管理的任何内容。这包括在这些视图与可用的多模式交互相结合之间任意切换的能力。目的是确定如何将结果应用于法医清醒和调查案件管理。想要一种方便可用的证据可视化,它的语义联系以及它的推理机制也是很自然的。因此,我们提出了一种可扩展的数字证据管理,可视化和评估,使用改进的交互式3D纪录片系统 - 无限空间系统 - (ISS)来表示,语义链接,并为可通过不同多模式导航的数字调查员提供可用的界面。使用计算机视觉技术的交互技术,包括手势,以及眼睛注视和音频。

URL

https://arxiv.org/abs/1808.00118

PDF

https://arxiv.org/pdf/1808.00118.pdf


Tags
3D Action Action_Localization Action_Recognition Activity Adversarial Agent Attention Autonomous Bert Boundary_Detection Caption Chat Classification CNN Compressive_Sensing Contour Contrastive_Learning Deep_Learning Denoising Detection Dialog Diffusion Drone Dynamic_Memory_Network Edge_Detection Embedding Embodied Emotion Enhancement Face Face_Detection Face_Recognition Facial_Landmark Few-Shot Gait_Recognition GAN Gaze_Estimation Gesture Gradient_Descent Handwriting Human_Parsing Image_Caption Image_Classification Image_Compression Image_Enhancement Image_Generation Image_Matting Image_Retrieval Inference Inpainting Intelligent_Chip Knowledge Knowledge_Graph Language_Model Matching Medical Memory_Networks Multi_Modal Multi_Task NAS NMT Object_Detection Object_Tracking OCR Ontology Optical_Character Optical_Flow Optimization Person_Re-identification Point_Cloud Portrait_Generation Pose Pose_Estimation Prediction QA Quantitative Quantitative_Finance Quantization Re-identification Recognition Recommendation Reconstruction Regularization Reinforcement_Learning Relation Relation_Extraction Represenation Represenation_Learning Restoration Review RNN Salient Scene_Classification Scene_Generation Scene_Parsing Scene_Text Segmentation Self-Supervised Semantic_Instance_Segmentation Semantic_Segmentation Semi_Global Semi_Supervised Sence_graph Sentiment Sentiment_Classification Sketch SLAM Sparse Speech Speech_Recognition Style_Transfer Summarization Super_Resolution Surveillance Survey Text_Classification Text_Generation Tracking Transfer_Learning Transformer Unsupervised Video_Caption Video_Classification Video_Indexing Video_Prediction Video_Retrieval Visual_Relation VQA Weakly_Supervised Zero-Shot