3D Coordinate Calculation and Pose Estimation of Power Meter based on Binocular Stereo Vision

Huang, Qingdan; Mo, Wenxiong; Pei, Liqiang; Zeng, Lian

doi:10.1145/3316615.3316655

Cited by 1 publication

(2 citation statements)

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“…In addition to the mere object detection within an image, it is also essential to identify the same object during a video or in different footage. The so-called object re-identification task is a very challenging and error-prone task, e.g., due to context-related problems like occlusion, noise, varying illumination, moving background objects, and ambiguity [ 15 , 16 ]. Li and Loy presented an approach that allows the re-identification of objects in successive frames, even if an object could not be identified in the frames in between [ 17 ].…”

Section: Related Workmentioning

confidence: 99%

“…If this depth information is available, the detections’ 3D position can be retrieved based on their bounding box position in the respective frames. This required depth information is available natively for binocular cameras that can capture 3D images [ 16 ]. For mono cameras, the depth information can be estimated as described in Section 3.3 .…”

Section: Crime Scene Analysis Framework: Processing Pipelinementioning

confidence: 99%

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Toward Mass Video Data Analysis: Interactive and Immersive 4D Scene Reconstruction

Kraus

Pollok

Miller

et al. 2020

Sensors

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The technical progress in the last decades makes photo and video recording devices omnipresent. This change has a significant impact, among others, on police work. It is no longer unusual that a myriad of digital data accumulates after a criminal act, which must be reviewed by criminal investigators to collect evidence or solve the crime. This paper presents the VICTORIA Interactive 4D Scene Reconstruction and Analysis Framework (“ISRA-4D” 1.0), an approach for the visual consolidation of heterogeneous video and image data in a 3D reconstruction of the corresponding environment. First, by reconstructing the environment in which the materials were created, a shared spatial context of all available materials is established. Second, all footage is spatially and temporally registered within this 3D reconstruction. Third, a visualization of the hereby created 4D reconstruction (3D scene + time) is provided, which can be analyzed interactively. Additional information on video and image content is also extracted and displayed and can be analyzed with supporting visualizations. The presented approach facilitates the process of filtering, annotating, analyzing, and getting an overview of large amounts of multimedia material. The framework is evaluated using four case studies which demonstrate its broad applicability. Furthermore, the framework allows the user to immerse themselves in the analysis by entering the scenario in virtual reality. This feature is qualitatively evaluated by means of interviews of criminal investigators and outlines potential benefits such as improved spatial understanding and the initiation of new fields of application.

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Section: Related Workmentioning

confidence: 99%

Section: Crime Scene Analysis Framework: Processing Pipelinementioning

confidence: 99%