Semantic content outweighs low-level saliency in determining children's and adults' fixation of movies

To make sense of the visual world, we need to move our eyes to focus regions of interest on the high-resolution fovea. Eye movements, therefore, give us a way to infer mechanisms of visual processing and attention allocation. Here, we examined age-related differences in visual processing by recording eye movements from 37 children (aged 6–14 years) and 10 adults while viewing three 5-min dynamic video clips taken from child-friendly movies. The data were analyzed in two complementary ways: (a) gaze based and (b) content based. First, similarity of scanpaths within and across age groups was examined using three different measures of variance (dispersion, clusters, and distance from center). Second, content-based models of fixation were compared to determine which of these provided the best account of our dynamic data. We found that the variance in eye movements decreased as a function of age, suggesting common attentional orienting. Comparison of the different models revealed that a model that relies on faces generally performed better than the other models tested, even for the youngest age group (<10 years). However, the best predictor of a given participant’s eye movements was the average of all other participants’ eye movements both within the same age group and in different age groups. These findings have implications for understanding how children attend to visual information and highlight similarities in viewing strategies across development

Global motion compensated visual attention-based video watermarking

Imperceptibility and robustness are two key but complementary requirements of any watermarking algorithm. Low-strength watermarking yields high imperceptibility but exhibits poor robustness. High-strength watermarking schemes achieve good robustness but often suffer from embedding distortions resulting in poor visual quality in host media. This paper proposes a unique video watermarking algorithm that offers a fine balance between imperceptibility and robustness using motion compensated wavelet-based visual attention model (VAM). The proposed VAM includes spatial cues for visual saliency as well as temporal cues. The spatial modeling uses the spatial wavelet coefficients while the temporal modeling accounts for both local and global motion to arrive at the spatiotemporal VAM for video. The model is then used to develop a video watermarking algorithm, where a two-level watermarking weighting parameter map is generated from the VAM saliency maps using the saliency model and data are embedded into the host image according to the visual attentiveness of each region. By avoiding higher strength watermarking in the visually attentive region, the resulting watermarked video achieves high perceived visual quality while preserving high robustness. The proposed VAM outperforms the state-of-the-art video visual attention methods in joint saliency detection and low computational complexity performance. For the same embedding distortion, the proposed visual attention-based watermarking achieves up to 39% (nonblind) and 22% (blind) improvement in robustness against H.264/AVC compression, compared to existing watermarking methodology that does not use the VAM. The proposed visual attention-based video watermarking results in visual quality similar to that of low-strength watermarking and a robustness similar to those of high-strength watermarking

Pupil Mimicry is the Result of Brightness Perception of the Iris and Pupil

Recent scientific investigations suggest that people automatically mimic each other’s pupil sizes during interaction. However, instead of being a social mimicry effect, it could also be the result of brightness perception. When observers look at individuals with dilated pupils, little of the brighter iris is visible, leading to the perception of a relatively low-illuminated eye region. In the current study we tested whether pupil mimicry remains present when pupils and irises are equalized for luminance values across pupil sizes. We tested several stimulus sets, including faces with static pupils that varied in size across images and dynamic pupils that changed in size over time in videos. Results showed that for traditional, not-luminance-equalized videos, participants’ pupil sizes adapted to the observed pupils, showing a pattern that is roughly in line with pupil mimicry. However, no such pupil response in line with mimicry was seen for static images (regardless of whether they were equalized for luminance) nor for luminance-equalized videos. These findings suggest that only salient, dynamic stimuli attract enough attention to the luminance in the eye region to evoke a pupillary response. However, although such responses suggest pupil mimicry, the underlying factor is the change in brightness within the eye as a function of pupil size rather than social mimicry

Attention Driven Solutions for Robust Digital Watermarking Within Media

As digital technologies have dramatically expanded within the last decade, content recognition now plays a major role within the control of media. Of the current recent systems available, digital watermarking provides a robust maintainable solution to enhance media security. The two main properties of digital watermarking, imperceptibility and robustness, are complimentary to each other but by employing visual attention based mechanisms within the watermarking framework, highly robust watermarking solutions are obtainable while also maintaining high media quality. This thesis firstly provides suitable bottom-up saliency models for raw image and video. The image and video saliency algorithms are estimated directly from within the wavelet domain for enhanced compatibility with the watermarking framework. By combining colour, orientation and intensity contrasts for the image model and globally compensated object motion in the video model, novel wavelet-based visual saliency algorithms are provided. The work extends these saliency models into a unique visual attention-based watermarking scheme by increasing the watermark weighting parameter within visually uninteresting regions. An increased watermark robustness, up to 40%, against various filtering attacks, JPEG2000 and H.264/AVC compression is obtained while maintaining the media quality, verified by various objective and subjective evaluation tools. As most video sequences are stored in an encoded format, this thesis studies watermarking schemes within the compressed domain. Firstly, the work provides a compressed domain saliency model formulated directly within the HEVC codec, utilizing various coding decisions such as block partition size, residual magnitude, intra frame angular prediction mode and motion vector difference magnitude. Large computational savings, of 50% or greater, are obtained compared with existing methodologies, as the saliency maps are generated from partially decoded bitstreams. Finally, the saliency maps formulated within the compressed HEVC domain are studied within the watermarking framework. A joint encoder and a frame domain watermarking scheme are both proposed by embedding data into the quantised transform residual data or wavelet coefficients, respectively, which exhibit low visual salience