A proto-object based saliency model in three-dimensional space

Hu, Brian; Kane-Jackson, Ralinkae; Niebur, Ernst

doi:10.1016/j.visres.2015.12.004

Cited by 26 publications

(24 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Slowness prototypes in ventral stream (Yousefi & Loo, 2015) . proto-object based on the saliency map (Hu et al 2016) . Coupling complex optical flows (Casile&Giese, 2005) .…”

Section: Resultsmentioning

confidence: 99%

“…Evidence of this hypothesis includes brain image studies and examination of the functional segregation light of the perceptual mechanisms subtending visual recognition and the same mechanism used for action [51]. Same methodology with slight extension used for proto-object model based on the saliency map, which involved depth information using the 3D eye tracking datasets presented by Hu et al (2016) [52], which was followed the evidence that supports the influence of eye movements on shape processing in the human visual system [6].…”

Section: Structural Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Biologically-Inspired Computational Neural Mechanism for Human Action/activity Recognition: A Review

Yousefi

Loo

2019

Electronics

View full text Add to dashboard Cite

Theoretical neuroscience investigation shows valuable information on the mechanism for recognizing the biological movements in the mammalian visual system. This involves many different fields of researches such as psychological, neurophysiology, neuro-psychological, computer vision, and artificial intelligence (AI). The research on these areas provided massive information and plausible computational models. Here, a review on this subject is presented. This paper describes different perspective to look at this task including action perception, computational and knowledge based modeling, psychological, and neuroscience approaches.

show abstract

“…Slowness prototypes in ventral stream (Yousefi & Loo, 2015) . proto-object based on the saliency map (Hu et al 2016) . Coupling complex optical flows (Casile&Giese, 2005) .…”

Section: Resultsmentioning

confidence: 99%

Section: Structural Methodsmentioning

confidence: 99%

Biologically-Inspired Computational Neural Mechanism for Human Action/activity Recognition: A Review

Yousefi

Loo

2019

Electronics

View full text Add to dashboard Cite

show abstract

“…In past studies, researchers have used binocular disparity to define the depth of different elements on discrete planes across the z-axis of the display (de la Rosa et al, 2008;Hu, Kane-Jackson, & Niebur, 2016;Marrara & Moore, 2000;Moore, Elsinger, & Lleras, 2001;Nakayama & Silverman, 1986;O'Toole & Walker, 1997). These studies have shown that attention can be focused at a particular depth;…”

Section: Discussionmentioning

confidence: 99%

The Foreground Bias: Differing impacts across depth on visual search in scenes

Lly¹,

Krzyś²,

Castelhano³

2019

Preprint

View full text Add to dashboard Cite

When you walk into a room, you perceive visual information that is both close to you and farther in depth. In the current study, we investigated how visual search is affected by information across scene depth and contrasted it with the effect of semantic scene context. Across two experiments, participants performed search for target objects appearing either in the foreground or background regions within scenes that were either normally configured or had semantically mismatched foreground and background contexts (Chimera scenes; Castelhano, Fernandes, & Theriault, 2018). In Experiment 1, we found participants had shorter latencies and fewer fixations to the target. This pattern was not explained by target size. In Experiment 2, a preview of the scene prior to search was added to better establish scene context prior to search. Results again show a Foreground Bias, with faster search performance for foreground targets. Together, these studies suggest processing differences across depth in scenes, with a preference for objects closer in space.

show abstract

“…Recent physiological studies reported that the cortical representation of 3D objects is mediated by 3D surface and 3D medial axis in monkey visual area IT ( Yamane et al, 2008 ; Hung et al, 2012 ). It might be interesting if those 3D representations were generated directly from the local BO signals ( Hu et al, 2016 ). This might be in line with the point that occlusion seems to be the most effective cue in the determination of the order of 3D depth.…”

Section: Discussionmentioning

confidence: 99%

Interactions Elicited by the Contradiction Between Figure Direction Discrimination and Figure-Ground Segregation

2018

View full text Add to dashboard Cite

Figure-ground (FG) segregation that separates an object from the rest of the image is a fundamental problem in vision science. A majority of neurons in monkey V2 showed the selectivity to border ownership (BO) that indicates which side of a contour owns the border. Although BO could be a precursor of FG segregation, the contribution of BO to FG segregation has not been clarified. Because FG segregation is the perception of the global region that belongs to an object, whereas BO determination provides the local direction of figure (DOF) along a contour, a spatial integration of BO might be expected for the generation of FG. To understand the mechanisms underlying the perception of figural regions, we investigated the interaction between the local BO determination and the global FG segregation through the quantitative analysis of the visual perception and the spatiotemporal characteristics of eye movements. We generated a set of novel stimuli in which translucency induces local DOF along the contour and global FG independently so that DOF and FG could be either consistent or contradictory. The perceptual responses showed better performance in DOF discrimination than FG segregation, supporting distinct mechanisms for the DOF discrimination and the FG segregation. We examined whether the contradiction between DOF and FG modulates the eye movement while participants judged DOF and FG. The duration of the first eye fixation was modulated by the contradiction during FG segregation but not DOF discrimination, suggesting a sequential processing from the BO determination to the FG segregation. These results of human perception and eye fixation provide important clues for understanding the visual processing for FG segregation.

show abstract

A proto-object based saliency model in three-dimensional space

Cited by 26 publications

References 51 publications

Biologically-Inspired Computational Neural Mechanism for Human Action/activity Recognition: A Review

Biologically-Inspired Computational Neural Mechanism for Human Action/activity Recognition: A Review

The Foreground Bias: Differing impacts across depth on visual search in scenes

Interactions Elicited by the Contradiction Between Figure Direction Discrimination and Figure-Ground Segregation

Contact Info

Product

Resources

About