Scene Fragments Research Articles

A Microscopic Traffic Flow Data Generation Method Based on an Improved DCGAN

Microscopic traffic flow data, an important input to virtual test scenarios for autonomous driving, are often difficult to obtain in large quantities to allow for batch testing. In this paper, a neural network for generating microscopic traffic flow scene fragments is proposed, which is improved by adding Gate Recurrent Units (GRU) to the discriminator of the Deep Convolutional Generative Adversarial Network (DCGAN) to enable it to better discriminate continuous data. Subsequently, this paper compares individual sample motion trajectories of the generated data using Grey Relational Analysis (GRA) and Dynamic Time Warping algorithm (DTW) at the microscopic scale, and evaluates the overall scenes generated using averaged statistics at the macroscopic scale. The results show that the method proposed in this paper can generate realistic microscopic traffic flow data very well and that the neural network proposed in this paper can generate better near-realistic microscopic traffic flow data than the original DCGAN under the evaluation metrics used in this paper.

Rapid contextualization of fragmented scene information in the human visual system

Real-world environments are extremely rich in visual information. At any given moment in time, only a fraction of this information is available to the eyes and the brain, rendering naturalistic vision a collection of incomplete snapshots. Previous research suggests that in order to successfully contextualize this fragmented information, the visual system sorts inputs according to spatial schemata, that is knowledge about the typical composition of the visual world. Here, we used a large set of 840 different natural scene fragments to investigate whether this sorting mechanism can operate across the diverse visual environments encountered during real-world vision. We recorded brain activity using electroencephalography (EEG) while participants viewed incomplete scene fragments at fixation. Using representational similarity analysis on the EEG data, we tracked the fragments’ cortical representations across time. We found that the fragments’ typical vertical location within the environment (top or bottom) predicted their cortical representations, indexing a sorting of information according to spatial schemata. The fragments’ cortical representations were most strongly organized by their vertical location at around 200 ​ms after image onset, suggesting rapid perceptual sorting of information according to spatial schemata. In control analyses, we show that this sorting is flexible with respect to visual features: it is neither explained by commonalities between visually similar indoor and outdoor scenes, nor by the feature organization emerging from a deep neural network trained on scene categorization. Demonstrating such a flexible sorting across a wide range of visually diverse scenes suggests a contextualization mechanism suitable for complex and variable real-world environments.

A neural mechanism for contextualizing fragmented inputs during naturalistic vision.

With every glimpse of our eyes, we sample only a small and incomplete fragment of the visual world, which needs to be contextualized and integrated into a coherent scene representation. Here we show that the visual system achieves this contextualization by exploiting spatial schemata, that is our knowledge about the composition of natural scenes. We measured fMRI and EEG responses to incomplete scene fragments and used representational similarity analysis to reconstruct their cortical representations in space and time. We observed a sorting of representations according to the fragments' place within the scene schema, which occurred during perceptual analysis in the occipital place area and within the first 200 ms of vision. This schema-based coding operates flexibly across visual features (as measured by a deep neural network model) and different types of environments (indoor and outdoor scenes). This flexibility highlights the mechanism's ability to efficiently organize incoming information under dynamic real-world conditions.

Comparing population receptive fields in human and macaque visual cortex

The population receptive field (pRF) modelling approach has been applied widely in human fMRI to inform the organization of both early and late stages of the cortical visual hierarchy. Recently, a pRF implementation was developed that allows for oriented and elliptical pRFs and demonstrated that dorsal and ventral divisions of early visual cortex (EVC) differentially sample visual space. Thus, differences between the larger dorsal and ventral visual processing streams may be set early on in the visual hierarchy. However, despite its common use, we do not yet understand how pRFs relate to the receptive fields of single neurons. Therefore, cross-species validation by means of comparative fMRI would go a long way to bridging the gap between single-unit recordings in monkeys and fMRI in humans. Here, we compare pRFs from dorsal and ventral divisions of EVC in both humans (n=12) and macaques (Macaca mulatta; n=2). Participants (both humans and macaques) fixated centrally while a bar aperture traversed gradually across the visual field revealing brief scene fragments. Data from both study populations were analyzed in AFNI using both standard (circular) and elliptical pRF models. Cross-validation analyses revealed that, similar to the human, the elliptical pRF model captured more variance in the time-course of macaque data than a circular pRF implementation. Further, pRF eccentricity was positively correlated with both pRF aspect ratio and pRF area, with the strength of correlation increasing generally as a function of position in the visual hierarchy. Also consistent with our human data, the average pRF angles of dorsal and ventral divisions of EVC are oriented differentially. Finally, we found that on average pRF size estimates in macaques tended to be larger than in humans, despite the overall similarity. Overall, these results reveal a very similar pattern of pRF properties between macaque and human visual cortex

Aligning 2.5D Scene Fragments With Distinctive Local Geometric Features and Voting-Based Correspondences

Aligning 2.5D views has been extensively explored in the past decades, where most prior works have concentrated on object data with complex structures. This paper presents a method to align real-word scene scans with challenging features such as noise, poor geometric information, and highly repeatable patterns. Our method consists of two modules: pairwise and multiview alignments. Key to the proposed pairwise alignment method is the rotational contour signature geometric feature and voting-based correspondence selection algorithm. The former promises strong discriminative power for 2.5D scene data, while the latter affords high-quality correspondences via a voting process for all raw feature matches using $L_{2}$ distance and point pair affinity constraints. For the multiview alignment method, we first use a connected graph algorithm to establish the connections of all 2.5D views for coarse merging; then, we propose a shape-growing iterative closest point algorithm for further refinement. Experiments are conducted on scene point cloud datasets addressing both the indoor and outdoor scenarios, whereby we demonstrate that the proposed pairwise alignment method clearly outperforms the state of the art. Moreover, the proposed multiview alignment method manages to put multiple unordered 2.5D scene fragments into a unified coordinate system automatically, accurately, and efficiently.

Missing the Drama: Staging Communities without Conflict

Missing the Drama:Staging Communities without Conflict Sharon Mazer (bio) We were in the Basement, a rough-and-ready theatre in Auckland, the largest city in New Zealand. The theatre has been built into the back of an old brick building on Queen Street, and is known for its funky appeal to younger, more diverse audiences than its mainstream neighbors in Auckland’s Arts Precinct.1 The Basement’s black box had been set up for an awkward, rather claustrophobic mix of cabaret and bench seating, almost engulfing a smallish rectangular stage planted on the long side and elevated about a foot off the floor. The audience was predominantly Māori and Pasifika, hip, and queer. The show was part of the Auckland Pride Festival (February 5–21, 2016), and the party was definitely perking along. The play was Puzzy, by Kiki (Kiana Rivera), a Hawaiian-based Samoan-Filipina lesbian playwright.2 The string of identifiers is essential here, because that’s what the play is essentially about: the coming-out story of Mele, a Samoan-Filipina Jehovah’s Witness who struggles against being labeled even as she comes to face up to her grandmother’s disapproval. The role of Mele was played by one young woman, Frankie Adams, while the other three women on stage (Nora Aati, Gaby Solomona, and Malia ‘Ahovelo) stepped in and out of the spotlight with her as friends and lovers, family and others. Across town at TAPAC (The Auckland Performing Arts Centre), the house was also packed, for At the End of My Hands: Stories for Deaf and Hearing Audiences.3 Onstage: six actors (four Deaf,4 two hearing) and a musician playing a variety of instruments, including piano and drums. The stage was bare except for three black cubes. Three translucent muslin panels hanging vertically upstage broke up the blackness of the box and offered opportunities for a bit of shadow play. At the End of My Hands was less scripted, more improvised than Puzzy. The stories were dispersed among the performers, a constellation of personal narratives, rather than centered on a singular protagonist, but the episodic structure was much the same: fragments of scenes in collage. Mixing sign, spoken word, and pantomime, the actors took turns describing and enacting episodes from life on the edge between Deaf and hearing communities. There were no “interpreters” as such, no translation or accommodation in either linguistic direction. With twice as many Deaf as hearing performers, those of us not fluent in New Zealand Sign Language had to employ a fair bit of empathy and imagination to keep up with the play. [End Page 7] At TAPAC, we were seated more conventionally, in rows facing the proscenium. But as at the Basement, it seemed that both the frame of the stage—what separated us from the performers—and the line between ordinary life and its theatricalized double had been transcended in the way Carol Martin describes in her introduction to Dramaturgy of the Real on the World Stage. In her words, “much of today’s dramaturgy of the real uses the frame of the stage not as a separation but as a communion of the real and the simulated; not as a distancing of fiction from nonfiction, but as a melding of the two.”5 Likewise, Hans-Thies Lehmann begins, in Postdramatic Theatre, by seeing the theatre as “a place where a unique intersection of aesthetically organized and everyday real life takes place.” 6 In these Auckland theatres what was performed seemed to be, in Lehmann’s words, “a real gathering.”7 Our sense of communion was intense, profound, contagious. Both Puzzy and At the End of My Hands were embraced by their audiences, many of whom clearly saw the actors speaking truths that were, if not their own, nonetheless resonant with their own experiences and values. There was a very real sense of grace in these gatherings. Both shows gave stage to communities who do not generally feature on the dominant cultural platforms of New Zealand, or anywhere else in the world. The productions were professional and proficient, well reviewed, with coverage in the city’s paper of record as well as on more specialist...

The Designing of Illustration Book for River Preservational for Children

The design project of this illustration book is backgrounded by pollutioned river phenomenon which is happening in Bandung, West Java, Indonesia. The pollution is mainly caused by the people behavior which are likely don't care about nature and neither have insight on what matters on it. This river pollution is reach at endangered level and can lead into health and social problem and affect on the environmental aesthetic as well. From that reasons above, education on people is needed to prevent the river from further destruction, recover its cleanness, everlast, and function on ecosystem balance.Target audience of this book is primary school children, who are mainly from family, live on the banks of the river. Children age was chosen because at this age they can rapidly absorb information around them. They also start to pre-change on their attitude, value, and behavior so it is expected to have impact on shaping their care-attitude toward environment at their current or future stage of life. This design project took sample on Cikapundung River located in Bandung Regency, West Java, Indonesia.The outcome of this design project is a picture-story book as an educational media, containing story about characters with implied moral messages. Scene fragments in time and ambience background story came with illustrations and narrations, purpose to communicate the education message. By that message, the target audiences are expected to emerge their attitude and changing behavior toward cleanness and everlast river environment arround them.

Searching regions of interest on vector local homogeneous scenes

A generalized solution of the problem of searching a scene's fragments, called the regions of interest, for the case when a set of spatial superposed images serves as the initial information about the scene, is proposed. A vector homogeneous random field is taken to be the scene model.

Density Determination by Water Displacement and Flotation: An Introductory Experiment in Forensic Chemistry

An introductory lab experiment has been developed for a nonscience major course in forensic chemistry, designed to introduce students to basic chemical principles within the context of interesting problem-solving scenarios. Students explore two different methods of density analysis and discover the practical uses and limitations of each. The experiment begins with a simple water-displacement exercise using common objects. Students discover problems involving accuracy and precision when calculating the densities of objects that displace very little water. The concept of flotation is introduced next, in which densities are compared, rather than measured directly, to determine the possibility of a common origin between two pieces of evidence. Students compare the densities of two simulated tire samples in 50 percent ethanol. Next, they perform a two-part analysis of glass and polymer fragments obtained from a simulated hit-and-run accident. Nonglass samples are compared using a saturated sodium chloride solution and water, and glass samples are analyzed in a series of bromoform–bromobenzene solutions. Students are able to successfully match five suspect fragments with the appropriate crime scene fragments using these methods.

A temporal same-object advantage in the tunnel effect: Facilitated change detection for persisting objects.

Meaningful visual experience requires computations that identify objects as the same persisting individuals over time, motion, occlusion, and featural change. This article explores these computations in the tunnel effect: When an object moves behind an occluder, and then an object later emerges following a consistent trajectory, observers irresistibly perceive a persisting object, even when the pre- and postocclusion views contrast featurally. This article introduces a new change detection method for quantifying percepts of the tunnel effect. Observers had to detect color changes in displays where several objects oscillated behind occluders and occasionally changed color. Across comparisons with several types of spatiotemporal gaps, as well as manipulations of occlusion versus implosion, performance was better when objects' kinematics gave the impression of a persisting individual. The results reveal a temporal same-object advantage: better change detection across temporal scene fragments bound into the same persisting object representations. This suggests that persisting objects are the underlying units of visual memory.

A database approach to hierarchical image storage and recognition

This paper presents the design of a model-based vision-recognition engine for implementing effective indexing schemes over a PC-based database system. The objective is to achieve robust recognition of planar contours or fragments of contours that are scale invariants of known models. Planar contours are partitioned into straight or slightly curved fragments (segments) and curved fragments (corners). The boundary problem is handled by using a constant-curvature criterion. To reduce the search space without pruning correct matches, a set of local and global descriptors is extracted from the model to enable indexed searching with different scaling, rotation, and translation from the model. Only a sub-set of matched classes with the highest frequencies are retained for finer matching which consists of distance matching, scale, and relative positioning. For partially occluded contours, fragments are individually matched by indexing over the local descriptors. Low-cost geometric inter-relationships among scene fragments are compared with those of the matched models, which allows consolidation of some matches, and invalidation of others. This approach enables a further reduction in the size of the matched classes. An evaluation of the method shows its ability to recognize entire contours, as well as partially occluded contours, from among a reasonably large dictionary. The approach proved to be tolerant with respect to partial occlusion, digitization noise, and slight variations in scale and spatial layout. The PC-based database approach to pattern recognition is shown to be efficient for real-time applications, and greatly simplifies the design.

Visual memories and mental images

A model is presented for the architecture of the neural networks which encode visual information for storage and which reconstruct iconic representations from storage representations. (Iconic representations are geometrically similar to projections of the objects they represent.) Each storage representation consists of a sequence of patterns derived while the eyes fixate at different positions in the visual field. Each pattern in the sequence has three components: (1) a control component which describes both where the eyes fixated and the size of the attended scene fragment; (2) a surface quality component which describes visual surface characteristics of the object; and (3) a spatial component which describes the spatial extent, spatial position (depth), surface orientation and visual flow (movement) of the surface having the specified surface characteristics. Prior to storage, all spatial components are transformed using a complex logarithmic mapping. As a consequence, stored spatial patterns are not iconic representations of the scene fragments they represent. Also, storage representations can be recognized and reconstructed at any desired size and orientation: they are size and orientation invariant. During reconstruction, each pattern in the storage representation is transformed back into an iconic representation using a complex exponential mapping. One consequence of the combined complex logarithmic and exponential mappings and the limited size of the storage representations is that the fidelity of the recalled information degrades exponentially from its centre. A neural network, called spatial memory, not only holds the partially reconstructed representation during recall, but also shifts it to remain in registration with the fragment currently being recalled and combined. The control system uses the control component of each stored pattern and knowledge of the size and orientation of the reconstruction to determine how to shift the partially reconstructed representation in spatial memory. Due to the decreasing fidelity from the centre to the perimeter of each reconstructed scene fragment, spatial memory only preserves information from overlapping fragments having the highest fidelity. It does so by maintaining and using fidelity information for each position in the reconstructed representation. Spatial memory can maintain a current stable representation of the visual world. It can also magnify, reduce, shift and rotate representations. The representations are therefore independent of their position in spatial memory. It is suggested that the representations held and processed by spatial memory correspond to the representations we call mental images and for this reason they are called mental images in the model.