Nonuniform video coding by means of multifoveal geometries

Rodríguez, Juan Antonio; García, Cristina; Bandera, Antonio; Hernández, Francisco

doi:10.1002/ima.10005

Cited by 5 publications

(11 citation statements)

References 12 publications

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“…The articles found with this problematic are the ones done by Camacho et al [22] and Rodriguez et al [23]. Regions of interest are encoded as a special case of elements belonging to more than one region within the foveated structures.…”

Section: Background Theorymentioning

confidence: 99%

“…There are works in robotic vision field related to reducing the amount of data to be encoded/decoded [7,13] and also in foveated systems for real-time video transmission [15,17,23]. In these applications, data are encoded with foveation, thus maintaining higher resolution in the areas of observation.…”

Section: Related Workmentioning

confidence: 99%

“…Among the works on multifoveation, we found several that perform the extraction of movement resources to infer knowledge about the context, for example, the ones of Dhavale and Itti [40], Camacho et al [22] and Rodrígez et al [23]. From these, there are some software capable of performing real-time multifoveated computing, but for this they use dedicated reprogrammable hardwares, such as FPGAs [22] which have excellent parallel processing capability.…”

Section: Related Workmentioning

confidence: 99%

“…We notice that only a few of the above works treats foveation in the context of point cloud [7] and a few others treats information redundancy in foveated images [22,23,42]. No work was found doing both at the same time.…”

Section: Related Workmentioning

confidence: 99%

“…Our proposal in this paper is based in the FPC [7] with the ideas of models of multifoveation 2D [22,23,40,41]. By grouping these two bases, it is proposed to create a model that reduces the processing time in the detection of objects, avoiding the processing of redundant regions generated by the overlap of the foveated structures, allowing a better performance in a multiple objects recognition task.…”

Section: Multifoveated Point Cloud-proposalmentioning

confidence: 99%

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Efficient 3D Objects Recognition Using Multifoveated Point Clouds

Oliveira

Souza

Fernandes

et al. 2018

Sensors

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Technological innovations in the hardware of RGB-D sensors have allowed the acquisition of 3D point clouds in real time. Consequently, various applications have arisen related to the 3D world, which are receiving increasing attention from researchers. Nevertheless, one of the main problems that remains is the demand for computationally intensive processing that required optimized approaches to deal with 3D vision modeling, especially when it is necessary to perform tasks in real time. A previously proposed multi-resolution 3D model known as foveated point clouds can be a possible solution to this problem. Nevertheless, this is a model limited to a single foveated structure with context dependent mobility. In this work, we propose a new solution for data reduction and feature detection using multifoveation in the point cloud. Nonetheless, the application of several foveated structures results in a considerable increase of processing since there are intersections between regions of distinct structures, which are processed multiple times. Towards solving this problem, the current proposal brings an approach that avoids the processing of redundant regions, which results in even more reduced processing time. Such approach can be used to identify objects in 3D point clouds, one of the key tasks for real-time applications as robotics vision, with efficient synchronization allowing the validation of the model and verification of its applicability in the context of computer vision. Experimental results demonstrate a performance gain of at least 27.21% in processing time while retaining the main features of the original, and maintaining the recognition quality rate in comparison with state-of-the-art 3D object recognition methods.

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Section: Background Theorymentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Multifoveated Point Cloud-proposalmentioning

confidence: 99%

See 3 more Smart Citations

Efficient 3D Objects Recognition Using Multifoveated Point Clouds

Oliveira

Souza

Fernandes

et al. 2018

Sensors

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Dynamic multifoveated structure for real-time vision tasks in robotic systems

Medeiros

Gomes

Clua

et al. 2019

J Real-Time Image Proc

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Foveation is a technique that allows real-time image processing by drastically reducing the amount of visual data without loosing essential information around some focused area. When a robot needs to pay attention at two or more regions of the image at the same time, e.g., for tracking two or more objects, multifoveation is necessary. In this case, computing features twice in the intersections between the different foveated structures, which could linearly increase the processing time, must be avoided. To solve this redundancy removal problem, we propose two algorithms. The first one is based on the previous calculation of redundant blocks and the second one is based on a pixel-by-pixel processing at execution time. Experimental results show a gain in processing time for the block-based model in comparison with the pixel-by-pixel and also of both in comparison with other approaches that sequentially calculate various single foveated images. Robotics vision and other tasks related to dynamic visual attention, as recognition, real-time surveillance, video transmission, and image rendering, are examples of applications that can rely on and strongly benefit from such model.

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