Lane detection is an important aspect of autonomous driving environment perception. Traditionally, lane detection has been regarded as a semantic segmentation task, and the geometric characteristics and position information of lanes have been ignored. Different from previous models, we proposed a model to capture the high-level semantic features and low-level position features of lanes by adopting two modules in the row and column. In the horizontal direction, we utilized line shape self-attention to capture the long-distance dependencies of lanes, which is crucial due to the slender shape of lanes, while reducing unnecessary computational resources to obtain irrelevant features. We used position information vectors encoding in the Key, Query, and Value modules in the transformer to enable considering the position information to explore potential location associations between lane and employed it for the vertical direction. In the Tusimple benchmark test, this method achieved an accuracy rate of 96.74%, demonstrating good competitiveness compared with existing methods.

This paper presents a systematic literature review of music technology tailored for blind and low vision (BLV) individuals.Music activities can be particularly beneficial for BLV people.However, a systematic approach to organizing knowledge on designing accessible technology for BLV people has yet to be attempted.We categorize the existing studies based on the type of technology and the extent of BLV people's involvement in the research.We identify six main categories of BLV people-oriented music technology and highlight four key trends in design goals.Based on these categories, we propose four general insights focusing on (1) spatial awareness, (2) access to information, (3) (non-verbal) communication, and (4) memory.The identified trends suggest that more empirical studies involving BLV people in real-world scenarios are needed to ensure that technological advancements can enhance musical experiences and social inclusion.This research proposes collaborative music technology and inclusive real-world testing with the target group as two key areas missing in current research.They serve as a foundational step in shifting the focus from "accessible technology" to "inclusive technology" for BLV individuals within the broader field of accessibility research.

CHI ’25, Yokohama, Japan

Chinese calligraphy offers fruitful visual structure not found in abstract/ figurative paintings or photographic images. It makes it well-suited for studying how personality shapes aesthetic preference, yet few works have explored this link. This paper introduces the first computational framework that models the link between viewer personality and Kai Shu calligraphic preference. It collects a dataset of Kai Shu calligraphy images, user preference scores, and Big Five personality traits. It extracts 160 structural feature descriptors from eight categories, such as stroke curvature, layout, and whitespace. Regression and attribution methods reveal five patterns, such as visual structure predicts perceived style, and that traits like Openness and Neuroticism influence preference patterns. High-Openness users prefer balanced, clean layouts. Low-Neuroticism users favor lighter, irregular forms. Some personality-feature pairs follow inverted-U trends, where moderate structural complexity leads to higher preference. These results connect cognitive traits with visual structure and support interpretable, personality aware modeling of aesthetic response. Our findings support personalized style discovery and open up new directions for interest-driven aesthetic education and digital preservation. Code available at https://github.com/tianchengliu18/kai2trait.

Artificial Intelligence-Generated Content (AIGC) tools have gradually been integrated into the daily workflow of UX practitioners. While existing research has explored the integration of AIGC tools in daily workflow, little is known about their impact on social dynamics within UX collaboration. We conducted four focus groups and eight semi-structured interviews with 26 UX practitioners to investigate how AIGC tools influence social dynamics in UX collaboration. Our findings indicated that AIGC tools not only mitigated conflicts but also introduced potential new conflicts. AIGC tools expanded the roles of UX practitioners and fostered a team culture characterized by exploring and discussing. Participants have higher expectations for AI-assisted design in user understanding and prototype evaluation, and team-motivated AI tools learning. Based on these findings, we discussed the benefits and concerns of conflict resolution through AIGC and the importance of teams in AI learning. Finally, we proposed several suggestions for future AI design research.

Tactile perception is a crucial channel for education in individuals with blindness and low vision (BLV), and beadwork is a low-cost and widely adopted tool in their educational practices. In this paper, we aim to explore what the field of Human-Computer Interaction (HCI) can learn from beadwork practices in relation to educational somatic experiences and tangible interaction. To understand how beadwork practices are enacted, we conducted in-class observations, semi-structured interviews, and focus groups with BLV students and teachers. Our results suggest that beadwork is an effective tool to foster personal development (e.g., mathematical and creativity skills) and social engagement (e.g., career development). Based on our findings, we offer insights into how beadwork can serve as a cost-effective material for HCI, particularly in the context of embodied cognition and soma design. Finally, we propose how state-of-the-art technology could be integrated to optimize the overall process.

Recent studies show the promise of VR in improving physical, cognitive, and emotional health of older adults. However, prior work on optimizing object selection and manipulation performance in VR was mostly conducted among younger adults. It remains unclear how older adults would perform such tasks compared to younger adults and the challenges they might face. To fill in this gap, we conducted two studies with both older and younger adults to understand their performances and user experiences of object selection and manipulation in VR respectively. Based on the results, we delineated interaction difficulties that older adults exhibited in VR and identified multiple factors, such as headset-related neck fatigue, extra head movements from out-of-view interactions, and slow spatial perceptions, that significantly decreased the motor performance of older adults. We further proposed design recommendations for improving the accessibility of direct interaction experiences in VR for older adults.

Style information, such as tone, mood, and genre of artworks, is important for museum visitors to appreciate them better. However, such information can be challenging for non-art specialists to comprehend in the short period that they view artworks. The sense of smell is instrumental for humans to assist their image memory, color, emotion, and shape association. However, it is rarely used in the appreciation of artworks. Taking Western landscape painting as an example, this research explores the following research questions (RQs): 1) How does the intervention of the sense of smell improve the acquisition of style information in paintings? 2) How does the intervention of the sense of smell enhance the immersion in painting appreciation? To answer RQs, we first recruited seven art specialists to participate in a co-design workshop to design a prototype of the virtual museum with olfactory intervention. We then conducted an experiment with 12 non-specialists who viewed several paintings in the VR museum while being exposed to olfactory stimuli that were designed to be correlated with the style information of the paintings. We found potential effects of smell stimuli on enhancing the perception of style information for non-art specialists. Moreover, we found that olfactory intervention has both positive and negative impacts on immersiveness. Finally, we provide design implications for future virtual museum design with olfactory stimuli.

The millimeter wave (mmWave) band has been considered as an effective way to meet the increasing traffic demand by sufficient bandwidth and high spatial reuse. The harsh propagation experienced at such high frequencies requires a dense base station deployment, which is not feasible to provide wired backhaul due to the unavailability of fiber drops. To address this issue, the integrated access and backhaul (IAB) architecture is proposed by the third generation partnership project (3GPP). In this paper, we investigate the spectrum and power allocation for IAB mmWave enabled cellular network to maximize the network capacity with considering the data rate requirements. A novel resource allocation scheme based on the sequential convex programming approach (RASCPA) is proposed. The simulation results show that our proposed scheme is superior to other schemes. The proposed scheme can increase the network capacity while satisfying the user data rate requirements.