Implicit Encoding Research Articles

GSEditPro: 3D Gaussian Splatting Editing with Attention‐based Progressive Localization

AbstractWith the emergence of large‐scale Text‐to‐Image(T2I) models and implicit 3D representations like Neural Radiance Fields (NeRF), many text‐driven generative editing methods based on NeRF have appeared. However, the implicit encoding of geometric and textural information poses challenges in accurately locating and controlling objects during editing. Recently, significant advancements have been made in the editing methods of 3D Gaussian Splatting, a real‐time rendering technology that relies on explicit representation. However, these methods still suffer from issues including inaccurate localization and limited manipulation over editing. To tackle these challenges, we propose GSEditPro, a novel 3D scene editing framework which allows users to perform various creative and precise editing using text prompts only. Leveraging the explicit nature of the 3D Gaussian distribution, we introduce an attention‐based progressive localization module to add semantic labels to each Gaussian during rendering. This enables precise localization on editing areas by classifying Gaussians based on their relevance to the editing prompts derived from cross‐attention layers of the T2I model. Furthermore, we present an innovative editing optimization method based on 3D Gaussian Splatting, obtaining stable and refined editing results through the guidance of Score Distillation Sampling and pseudo ground truth. We prove the efficacy of our method through extensive experiments.

Two-Stream Graph Convolutional Network-Incorporated Latent Feature Analysis

Historical Quality-of-Service (QoS) data describing existing user-service invocations are vital to understanding user behaviors and cloud service conditions. Collaborative Filtering (CF) models based on Matrix Factorization (MF) have proven to be highly efficient in performing representation learning in QoS data. However, its performance is hindered by its linear inherence and implicit encoding of collaborative QoS signal. To address this critical issue, we present a novel approach in this paper, dubbed as <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <u>T</u></b> wo-stream <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <u>G</u></b> raph convolutional network-incorporated <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <u>L</u></b> atent <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <u>F</u></b> eature <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <u>A</u></b> nalysis (TGLFA). The proposed TGLFA is significantly different from previous approaches to representation learning in QoS data in the following three aspects. First, it constructs a multilayer fully-connected network to capture the attribute characteristics representing the nonlinear latent features of service. Second, TGLFA constructs a biparty graph to represent the user-service interactions, where the light graph convolutional network is adopted to acquire the high-order connectivity in QoS data. Last, Aiming to improve computational efficiency, the proposed approach considers the mechanism for data density-oriented modeling when building the input and output layers. Detailed experimental results on eight large-scale cases constructed on two real QoS datasets demonstrate that the proposed TGLFA significantly outperforms its state-of-the-art peers in both estimation accuracy for missing QoS data and computational efficiency. The notable results show that TGLFA is a novel and effective approach to QoS data representation learning.

Alterations of theta power and synchrony during encoding in young adult binge drinkers: Subsequent memory effects associated with retrieval after 48 h and 6 months.

Young emerging adults commonly engage in binge drinking which is associated with a range of neurocognitive deficits, including memory impairments. However, evidence on neural oscillations mediating episodic memory in this population is lacking. To address this gap, we recorded theta oscillatory activity in young binge (BDs) and light drinkers (LDs) during memory encoding and analyzed it prospectively as a function of subsequent retrieval. Theta underlies successful encoding of novel items in memory through corticolimbic integration. Subsequent memory effects (SMEs) are reflected in stronger theta activity during encoding of the items that are later remembered compared to those that are later forgotten. In the present study, 23 BDs (age: 23.3 ± 3.3) and 24 LDs (age: 23.4 ± 3.3) rated emotionally evocative images with negative, positive, and neutral themes during implicit encoding. They performed a recognition memory task on two follow-up occasions after a short (48 h), and long retention delay (6 months). Electroencephalography (EEG) signal was recorded during the encoding session and analyzed in time-frequency domain with Morlet wavelets in theta band (4-7 Hz). To evaluate SMEs, the event-related theta oscillations acquired during encoding were analyzed based on recognition outcomes after the two retention intervals. The BD and LD groups did not differ on recognition memory. However, BDs showed attenuated event-related theta power during encoding of images that were successfully retained after 6 months compared to LDs. In addition, theta synchronous activity between frontal and left posterior regions during encoding successfully predicted recognition of the images after both retention delays in LDs but not in BDs. These SMEs on theta power and synchrony correlated negatively with high-intensity drinking in the previous 6 months. No differences between men and women were observed for any analysis. It has been well established that long-range neural synchrony between cortical and limbic nodes underlies successful memory encoding and retention which, in turn, depends on neural excitation/inhibition (E/I) balance. Given that binge drinking is associated with E/I dysregulation, the observed SME deficiencies are consistent with other evidence of neural hyperexcitability in BDs, and may be indicative of increased risk of developing alcohol use disorders.

Large motion anime head animation using a cascade pose transform network

We study the problem of talking head animation from a single image where a target anime talking head is generated to mimic the change of facial expression and head movement of source anime characters. Most existing methods focus on generating talking heads from real humans. However, few efforts have been made to create anime talking head. Compared with human head generation, the key challenges of anime head generation are: how to align the pose and facial expression of the target head with that of the source head without explicit facial landmarks. To address this, we propose CPTNetV2, a cascaded pose transform network that unifies face pose transformation and head pose transformation. At the core of CPTNetV2 is the implicit encoding of facial changes and head movement by a pose vector. Given the pose vector, we introduce a mask generator to animate facial expression (e.g., close eyes and open mouth) and a grid generator to simulate head movement, followed by a fusion module to generate talking heads. To tackle large displacement and improve the quality of generation, we further design a details inpainting module with pose vector decomposition to reduce the receptive field of network required for pose transformation. In particular, we collect an anime talking head dataset AniHead-2K that includes around 2000 anime characters with different face/head poses. Extensive experiments on AniHead-2K demonstrate that CPTNetV2 can achieve arbitrary pose transformation conditioned on the target pose vector and outperforms other state-of-the-art methods. We also verify the effectiveness of each module through ablative studies. Additional results show that CPTNetV2 has good generalization and is applicable to generate anime talking head even based on human videos. The dataset will be made available at: https://github.com/zhangjiale487/AniHead-2K.

Mapping of Language-and-Memory Networks in Patients With Temporal Lobe Epilepsy by Using the GE2REC Protocol.

Preoperative mapping of language and declarative memory functions in temporal lobe epilepsy (TLE) patients is essential since they frequently encounter deterioration of these functions and show variable degrees of cerebral reorganization. Due to growing evidence on language and declarative memory interdependence at a neural and neuropsychological level, we propose the GE2REC protocol for interactive language-and-memory network (LMN) mapping. GE2REC consists of three inter-related tasks, sentence generation with implicit encoding (GE) and two recollection (2REC) memory tasks: recognition and recall. This protocol has previously been validated in healthy participants, and in this study, we showed that it also maps the LMN in the left TLE (N = 18). Compared to healthy controls (N = 19), left TLE (LTLE) showed widespread inter- and intra-hemispheric reorganization of the LMN through reduced activity of regions engaged in the integration and the coordination of this meta-network. We also illustrated how this protocol could be implemented in clinical practice individually by presenting two case studies of LTLE patients who underwent efficient surgery and became seizure-free but showed different cognitive outcomes. This protocol can be advantageous for clinical practice because it (a) is short and easy to perform; (b) allows brain mapping of essential cognitive functions, even at an individual level; (c) engages language-and-memory interaction allowing to evaluate the integrative processes within the LMN; (d) provides a more comprehensive assessment by including both verbal and visual modalities, as well as various language and memory processes. Based on the available postsurgical data, we presented preliminary results obtained with this protocol in LTLE patients that could potentially inform the clinical practice. This implies the necessity to further validate the potential of GE2REC for neurosurgical planning, along with two directions, guiding resection and describing LMN neuroplasticity at an individual level.

Image or Identity? Only Super-recognizers’ (Memor)Ability is Consistently Viewpoint-Invariant

A face’s memorability refers to the unique combination of visual features facilitating its recognition. Despite considerable variation in face recognition ability amongst the general population, individuals show substantial concordance regarding faces’ memorability. This agreement persists, though reduced, when the viewpoints across which identities are seen at encoding and recognition differ. Consequently, individuals must extract some invariant facial information during recognition, robust to changes in viewpoint, to do so consistently (i.e. as a function of stimulus memorability). However, the extent of such consistency remains unclear. Therefore, in two experiments we tested recognition of (i) implicitly encoded face images and (ii) explicitly encoded identities in a group of control observers against a group of “Super-Recognizers” (SRs) possessing exceptional face processing skills (Ramon, 2021). Novel “With or Without You” (WoWY) resampling analyses assessed the consistency of SRs relative to control observers, simultaneously providing measures of intraindividual consistency. When implicit encoding was surreptitiously solicited (Experiment 1), recognition of studied images was comparable between groups. Yet, when encoding was explicitly solicited (Experiment 2), SRs more accurately recognized identities across viewpoint changes than controls. Critically, image-dependent information could only inform recognition in the first experiment, whereas viewpoint-invariant information could inform recognition equally in both. Individual observers’ performance profiles reveal that only SRs memorability-related performance was consistent between experiments. Overall, SRs’ unique capacity for recognizing faces based on viewpoint-invariant information is rooted in fundamentally more robust representations of identity. These results invite a reinterpretation of face memorability describing viewpoint-invariant information, diagnostic of facial identity representations in memory. <strong>Highlights</strong> <ul><li>Super-Recognizers (SRs) do not uniformly recognize face images better than controls; both SRs and control observers tend to recognize high- and low-memorability stimuli equally well.</li><li>Novel “With or Without You” analyses, combining split-half resampling and permutation techniques, revealed inter- and intra-individual consistency in recognition memory.</li><li>SRs excelled at explicit (but not implicit) learning of facial identities relative to controls when viewpoint-invariant information was task-relevant.</li><li>SRs consistently represent faces with identity-based (viewpoint-invariant) memorability, while controls use either image- or identity-based representations.<br />The finding that consistency of identity-based memorability is relatively unique to SRs suggests that it constitutes a potential marker of overall face recognition ability.</li></ul>

Effects of emotionally incongruent musical excerpts on memory retrieval

Music’s power to trigger memories has rarely been tested; in particular, it is not clear what mechanisms govern memory retrieval elicited by musical cues. Previous research has suggested that memory retrieval is underpinned by two mechanisms: (1) distinctiveness—the probability that a cue will retrieve a memory declines with the number of stimuli previously encoded with that same cue and (2) incongruence—a cue encoded with emotionally incongruent targets triggers more memories of the stimuli associated with it than a cue encoded with emotionally congruent stimuli. Our participants experienced an implicit encoding phase where they were presented with auditory-visual pairs of stimuli (pieces of music and images of facial expressions). In the retrieval phase, participants were asked to remember encoded stimuli triggered by music. As expected, musical cues encoded with emotionally incongruent facial expressions triggered more memories than cues encoded with congruent facial expressions. Contrary to our prediction and to previous findings, music from distinctive pairs of stimuli triggered fewer memories than cue pairs displayed multiple times in the encoding phase. Our finding suggests that the manipulation of stimuli at encoding is crucial when using musical cues to trigger memories.

Dynamics of nonlinguistic statistical learning: From neural entrainment to the emergence of explicit knowledge

Humans are highly attuned to patterns in the environment. This ability to detect environmental patterns, referred to as statistical learning, plays a key role in many diverse aspects of cognition. However, the spatiotemporal neural mechanisms underlying implicit statistical learning, and how these mechanisms may relate or give rise to explicit learning, remain poorly understood. In the present study, we investigated these different aspects of statistical learning by using an auditory nonlinguistic statistical learning paradigm combined with magnetoencephalography. Twenty-four healthy volunteers were exposed to structured and random tone sequences, and statistical learning was quantified by neural entrainment. Already early during exposure, participants showed strong entrainment to the embedded tone patterns. A significant increase in entrainment over exposure was detected only in the structured condition, reflecting the trajectory of learning. While source reconstruction revealed a wide range of brain areas involved in this process, entrainment in areas around the left pre-central gyrus as well as right temporo-frontal areas significantly predicted behavioral performance. Sensor level results confirmed this relationship between neural entrainment and subsequent explicit knowledge. These results give insights into the dynamic relation between neural entrainment and explicit learning of triplet structures, suggesting that these two aspects are systematically related yet dissociable. Neural entrainment reflects robust, implicit learning of underlying patterns, whereas the emergence of explicit knowledge, likely built on the implicit encoding of structure, varies across individuals and may depend on factors such as sufficient exposure time and attention.

Perception of atomic speech

Natural speech signals are continuous and have great redundancy in time, which is learned by human beings and guarantees speech comprehension even in challenging circumstances. This work develops a sound synthesis method to study some time-related characteristics of the human auditory system. The temporal information within the individual frequency band of a speech is down-sampled using Gaussian-shaped pulses and then recombined into a new sound which may have some remaining intelligibility or feasible phonetic features. The “atomic” sound is coined to the sound with an extremely spectral-temporally sparse spectrogram generated using the method. A battery of speech perception tests was administered in normal-hearing listeners. Results show that (1) atomic sounds from clear speech can be understood as speech, although the listeners often reported a feeling of water sound textures; (2) the temporal and spectral resolution could be traded off in the atomic speech comprehension; and (3) only one maximum envelope value preserved among a 32-channel filter-bank at a rate of 400 Hz was surprisingly adequate for speech understanding, which indicates that the brain can organize the only spectral peak within each short duration no longer than 2.5-ms into sentence understanding without either explicit or implicit encoding of the first three formants.

Edge Enhanced Implicit Orientation Learning With Geometric Prior for 6D Pose Estimation

Estimating 6D poses of rigid objects from RGB images is an important but challenging task. This is especially true for textureless objects with strong symmetry, since they have only sparse visual features to be leveraged for the task and their symmetry leads to pose ambiguity. The implicit encoding of orientations learned by autoencoders [31], [32] has demonstrated its effectiveness in handling such objects without requiring explicit pose labeling. In this letter, we further improve this methodology with two key technical contributions. First, we use edge cues to complement the color images with more discriminative features and reduce the domain gap between the real images for testing and the synthetic ones for training. Second, we enhance the regularity of the implicitly learned pose representations by a self-supervision scheme to enforce the geometric prior that the latent representations of two images presenting nearby rotations should be close too. Our approach achieves the state-of-the-art performance on the T-LESS benchmark in the RGB domain; its evaluation on the LINEMOD dataset also outperforms other synthetically trained approaches. Extensive ablation tests demonstrate the improvements enabled by our technical designs. Our code is publicly available for research use. <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">**</sup> The code is available at https://github.com/fylwen/EEGP-AAE.

Implicit argumentation and persuasion

Abstract The paper provides evidence that linguistic strategies based on the implicit encoding of information are effective means of deceptive argumentation and manipulation, as they can ease the acceptance of doubtful arguments by distracting addressees’ attention and by encouraging shallow processing of doubtful contents. The persuasive and manipulative functions of these rhetorical strategies are observed in commercial and political propaganda. Linguistic implicit strategies are divided into two main categories: the implicit encoding of content, mainly represented by implicatures and vague expressions, and the implicit encoding of responsibility, mainly represented by presuppositions and topics. The paper also suggests that the amount of persuasive implicitness contained in texts can be measured. For this purpose, a measuring model is proposed and applied to some Italian political speeches. The possible social usefulness of this approach is showed by sketching the operation of a website in which the measuring model is used to monitor contemporary political speeches.

The self-reference effect on memory is not diminished in autism: Three studies of incidental and explicit self-referential recognition memory in autistic and neurotypical adults and adolescents.

Three experiments investigated the extent to which (a) individuals with autism show a self-reference effect (i.e., better memory for self-relevant information), and (b) the size of the self-reference effect is associated with autism traits. Participants studied trait adjectives in relation to their own name (self-referent) or a celebrity’s name (other-referent) under explicit and incidental/implicit encoding conditions. Explicit encoding involved judging whether the adjectives applied to self or other (denoted by proper names). Implicit encoding involved judging whether the adjectives were presented to the right or left of one’s own or a celebrity’s name. Recognition memory for the adjectives was tested using a yes/no procedure. Experiment 1 (individual differences; N = 257 neurotypical adults) employed the Autism-spectrum Quotient as a measure of autistic traits. Experiments 2 (n = 60) and 3 (n = 52) involved case-control designs with closely matched groups of autistic and neurotypical adults and children/adolescents, respectively. Autistic traits were measured using the Autism-spectrum Quotient and Social Responsiveness Scale, respectively. In all experiments, a significant self-reference effect was observed in both explicit and implicit encoding conditions. Most importantly, however, there was (a) no significant relation between size of the self-reference effect and number of autistic traits (Experiments 1, 2, and 3), and (b) no significant difference in the size of the self-reference effect between autistic and neurotypical participants (Experiments 2 and 3). In these respects, Bayesian analyses consistently suggested that the data supported the null hypothesis. These results challenge the notion that subjective or objective self-awareness are impaired in autism.

Conditional automaticity: interference effects on the implicit memory retrieval process

Many studies have indicated that executing a secondary task during encoding has little influence on implicit memory (priming effect). However, relatively few studies have discussed the effect of interference on implicit memory during retrieval. Our previous studies found asymmetry between implicit encoding and retrieval processes, with the priming effect disrupted by retrieval interference. Therefore, the present study investigated why and how the priming effect is affected by interference at retrieval. We adopted a dual-task paradigm, with a lexical decision task as the memory task and an odd-even decision task as the interference task. The effect of interference during retrieval was assessed by comparing the performance in the interference condition with that in the full-attention condition. In Experiment 1, we observed that the priming effect was absent in the synchronous retrieval interference condition. In Experiment 2, asynchronous interference was also found to block the priming effect. To verify the assumption that the priming effect is sensitive to attentional resource competition during retrieval, we used two different manipulations (an extended stimulus interval in the dual-task paradigm, Experiment 3, and an interference inhibition manipulation, Experiment 4) known to reduce attentional distraction. In these experiments, the priming effect was protected from interference effects. We suggest that implicit memory retrieval could be regarded as a conditional automatic process that depends on a configuration of the cognitive system by attention and task sets. If the limited resources are occupied by another task, the implicit retrieval process can be impacted.

Predictive Modulation of Corticospinal Excitability and Implicit Encoding of Movement Probability in Schizophrenia.

The ability to infer from uncertain information is impaired in schizophrenia and is associated with hallucinations and false beliefs. The accumulation of information is a key process for generating a predictive internal model, which statistically estimates an outcome from a specific situation. This study examines if updating the predictive model by the accumulation of information in absence of feedback is impaired in schizophrenia. We explored the implicit adaptation to the probability of being instructed to perform a movement (33%-Go, 50%-Go, or 66%-Go) in a Go/NoGo task in terms of reaction times (RTs), electromyographic activity, and corticospinal excitability (CSE) of primary motor cortex (M1). CSE was assessed at two time points to evaluate prediction of the upcoming instruction based on previously accumulated information: at rest (preceding the warning signal) and at the Go/NoGo signal onset. Three groups were compared: patients with schizophrenia (n = 20), unaffected siblings (n = 16), and healthy controls (n = 20). Controls and siblings showed earlier movement onset and increased CSE with higher Go probability. CSE adaptation seemed long-lasting, because the two CSE measures, at least 1500 ms apart, strongly correlated. Patients with schizophrenia failed to show movement onset (RT) adaptation and modulation of CSE. In contrast, all groups decreased movement duration with increasing Go probability. Modulation of CSE in the anticipatory phase of the potential movement reflected the estimation of upcoming response probability in unaffected controls and siblings. Impaired modulation of CSE supports the hypothesis that implicit adaptation to probabilistic context is altered in schizophrenia.

The Impact of Viewing Time to Internal Facial Features on Face Recognition Performance Following Implicit and Explicit Encoding

The Impact of Viewing Time to Internal Facial Features on Face Recognition Performance Following Implicit and Explicit Encoding

A map of abstract relational knowledge in the human hippocampal-entorhinal cortex.

The hippocampal-entorhinal system encodes a map of space that guides spatial navigation. Goal-directed behaviour outside of spatial navigation similarly requires a representation of abstract forms of relational knowledge. This information relies on the same neural system, but it is not known whether the organisational principles governing continuous maps may extend to the implicit encoding of discrete, non-spatial graphs. Here, we show that the human hippocampal-entorhinal system can represent relationships between objects using a metric that depends on associative strength. We reconstruct a map-like knowledge structure directly from a hippocampal-entorhinal functional magnetic resonance imaging adaptation signal in a situation where relationships are non-spatial rather than spatial, discrete rather than continuous, and unavailable to conscious awareness. Notably, the measure that best predicted a behavioural signature of implicit knowledge and blood oxygen level-dependent adaptation was a weighted sum of future states, akin to the successor representation that has been proposed to account for place and grid-cell firing patterns.

Implicit encoding of extrinsic object properties in stored representations mediating recognition: Evidence from shadow-specific repetition priming

This study investigated whether, and under what conditions, stored shape representations mediating recognition encode extrinsic object properties that vary according to viewing conditions. This was examined in relation to cast shadow. Observers (N=90) first memorised a subset of 3D multi-part novel objects from a limited range of viewpoints rendered with either no shadow, object internal shadow, or both object internal and external (ground) plane shadow. During a subsequent test phase previously memorised targets were discriminated from visually similar distractors across learned and novel views following brief presentation of a same-shape masked prime. The primes contained either matching or mismatching shadow rendering from the training condition. The results showed a recognition advantage for objects memorised with object internal shadow. In addition, objects encoded with internal shadow were primed more strongly by matching internal shadow primes, than by same shape primes with either no shadow or both object internal and external (ground) shadow. This pattern of priming effects generalises to previously unseen views of targets rendered with object internal shadow. The results suggest that the object recognition system contains a level of stored representation at which shape and the extrinsic object property of cast shadow are bound. We propose that this occurs when cast shadow cannot be discounted during perception on the basis of external cues to the scene lighting model.

Explicit Embeddings for Nearest Neighbor Search with Mercer Kernels

Many approximate nearest neighbor search algorithms operate under memory constraints, by computing short signatures for database vectors while roughly keeping the neighborhoods for the distance of interest. Encoding procedures designed for the Euclidean distance have attracted much attention in the last decade. In the case where the distance of interest is based on a Mercer kernel, we propose a simple, yet effective two-step encoding scheme: first, compute an explicit embedding to map the initial space into a Euclidean space; second, apply an encoding step designed to work with the Euclidean distance. Comparing this simple baseline with existing methods relying on implicit encoding, we demonstrate better search recall for similar code sizes with the chi-square kernel in databases comprised of visual descriptors, outperforming concurrent state-of-the-art techniques by a large margin.

The role of motor response in implicit encoding: Evidence from intertrial priming in pop-out search

Perception and motor control jointly act to meet our current needs. Recent evidence shows that the generation of motor action significantly affects perception. Here, we examined the role of motor response in inter-trial priming, namely, in Priming of Pop-out (PoP): when searching for a singleton target, performance is improved when the target and distractors features repeat on consecutive search trials than when they switch. Although recent studies have shown an interaction between motor response and PoP, the role of motor action on priming has not been fully characterized. Here we investigated whether motor action is necessary during encoding, for PoP to be observed. On go trials, observers searched for a color singleton target and responded to its shape, while on no-go trials they passively watched the display instead of responding to the target. We observed PoP even when the previous trial had been a no-go trial, suggesting that encoding of search-relevant attributes in pop-out displays is not contingent on motor response. Nevertheless, the repetition effect was larger after a go trial than after a no-go trial, supporting the dual-stage model of PoP, according to which this effect involves both a perceptual and a motor component.

Enhanced visualisation for minimally invasive surgery

Endoscopes used in minimally invasive surgery provide a limited field of view, thus requiring a high degree of spatial awareness and orientation. Attempts at expanding this small, restricted view with previously observed imagery have been made by researchers and is generally known as image mosaicing or dynamic view expansion. For minimally invasive endoscopy, SLAM-based methods have been shown to have potential values but have yet to address effective visualisation techniques. The live endoscopic video feed is expanded with previously observed footage. To this end, a method that highlights the difference between actual camera image and historic data observed earlier is proposed. Old video data is faded out to grey scale to mimic human peripheral vision. Specular highlights are removed with the help of texture synthesis to avoid distracting visual cues. The method is further evaluated on in vivo and phantom sequences by a detailed user study to examine the ability of the user in discerning temporal motion trajectories while visualising the expanded field of view, a feature that is of practical value for enhancing spatial awareness and orientation. The difference between historic data and live video is integrated effectively. The use of a single texture domain generated by planar parameterisation is demonstrated for view expansion. Specular highlights can be removed through texture synthesis without introducing noticeable artefacts. The implicit encoding of motion trajectory of the endoscopic camera visualised by the proposed method facilitates both global awareness and temporal evolution of the scene. Dynamic view expansion provides more context for navigation and orientation by establishing reference points beyond the camera's field of view. Effective integration of visual cues is paramount for concise visualisation.