Towards explainable deep visual saliency models

Malladi, Sai Phani Kumar; Mukherjee, Jayanta; Larabi, Mohamed–Chaker; Chaudhury, Santanu

doi:10.1016/j.cviu.2023.103782

Cited by 2 publications

(1 citation statement)

References 31 publications

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“…Another approach is a motion-control strategy driven by a salient point, which can make up for these shortages. Researchers have made significant progress in saliency-detection algorithms, including classical algorithms [33][34][35] and deep neural networks [36][37][38]. The results of saliency detection are increasingly aligning with human eye selective attention.…”

Section: Introductionmentioning

confidence: 99%

The Design and Control of a Biomimetic Binocular Cooperative Perception System Inspired by the Eye Gaze Mechanism

Qin,

Xia,

et al. 2024

Biomimetics

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Research on systems that imitate the gaze function of human eyes is valuable for the development of humanoid eye intelligent perception. However, the existing systems have some limitations, including the redundancy of servo motors, a lack of camera position adjustment components, and the absence of interest-point-driven binocular cooperative motion-control strategies. In response to these challenges, a novel biomimetic binocular cooperative perception system (BBCPS) was designed and its control was realized. Inspired by the gaze mechanism of human eyes, we designed a simple and flexible biomimetic binocular cooperative perception device (BBCPD). Based on a dynamic analysis, the BBCPD was assembled according to the principle of symmetrical distribution around the center. This enhances braking performance and reduces operating energy consumption, as evidenced by the simulation results. Moreover, we crafted an initial position calibration technique that allows for the calibration and adjustment of the camera pose and servo motor zero-position, to ensure that the state of the BBCPD matches the subsequent control method. Following this, a control method for the BBCPS was developed, combining interest point detection with a motion-control strategy. Specifically, we propose a binocular interest-point extraction method based on frequency-tuned and template-matching algorithms for perceiving interest points. To move an interest point to a principal point, we present a binocular cooperative motion-control strategy. The rotation angles of servo motors were calculated based on the pixel difference between the principal point and the interest point, and PID-controlled servo motors were driven in parallel. Finally, real experiments validated the control performance of the BBCPS, demonstrating that the gaze error was less than three pixels.

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