Guided by Augmented Reality: The Results of Multiple Experiments Conducted to Enhance the Visitor Experience at a Culturally Historic Site | Chapter 2 | Science and Technology - Recent Updates and Future Prospects Vol. 2

 

In recent years, museums and historic sites have expanded their reach beyond traditional audiences by embracing innovative digital display technologies. Among these technologies, virtual, mixed, and augmented reality (AR) have gained prominence in society. These “virtual history” exhibits aim to bring historical narratives to life, allowing visitors to engage with the past in novel ways. However, the successful implementation of AR in cultural heritage contexts requires careful consideration of usability factors and alignment with media creators’ intended meanings.

Our research investigates the use of various AR technologies within cultural heritage applications. Specifically, we conducted multiple experiments at a historic fort in upstate New York, evaluating the impact of digital display technology on-site visitors. By analyzing user experiences, we aimed to understand how AR enhances cultural exploration and engagement.

Key areas of focus include:

•          Usability Factors: We examined how visitors interacted with AR applications, considering ease of use, navigation, and overall satisfaction.

•          Human-Computer Interaction: Understanding how users engage with AR interfaces and interpret historical content.

•          Evaluation: Assessing the effectiveness of AR displays in conveying cultural heritage information.

Our findings contribute to the ongoing discourse on leveraging AR for cultural preservation and education. By bridging the gap between physical artifacts and virtual imagery, AR can enrich visitors’ understanding of historical contexts. As museums and heritage sites continue to embrace digital technologies, thoughtful design and evaluation are crucial for creating meaningful and immersive experiences.

In summary, this research sheds light on the potential of AR to augment cultural exploration, enhance visitor engagement, and breathe new life into historical narratives. By blending technology and heritage, we pave the way for a more dynamic and accessible appreciation of our shared past.

 

Author(s)details:-

 

Dr. Damian Schofield
Department of Computer Science, State University of New York, Oswego, New York, USA.

 

Paul Lear
Fort Ontario State Historic Site, Oswego, New York, USA.

 

Daniel Hufnal
Department of Computer Science, State University of New York, Oswego, New York, USA.

 

Theodore Johnson
Department of Computer Science, State University of New York, Oswego, New York, USA.

 

Sarah Colletta
Department of Computer Science, State University of New York, Oswego, New York, USA.

 

Pranay Chapagain
Department of Computer Science, State University of New York, Oswego, New York, USA.

 

Please See the book here :- https://doi.org/10.9734/bpi/strufp/v2/8585E

Real Time Static Gesture Recognition Using Time of Flight Camera: Scientific Approach | Chapter 7 | Emerging Trends in Engineering Research and Technology Vol. 2

Hand gesture recognition is challenging task in machine vision due to similarity between inter class samples and high amount of variation in intra class samples. The gesture recognition independent of light intensity, independent of color has drawn some attention due to its requirement where system should perform during night time also. This paper provides an insight into dynamic hand gesture recognition using depth data and images collected from time of flight camera. It provides user interface to track down natural gestures. The area of interest and hand area is first segmented out using adaptive thresholding and region labeling. It is assumed that hand is the closet object to camera. A novel algorithm is proposed to segment the hand region only. The noise due to ToF camera measurement is eliminated by preprocessing algorithms. There are two algorithms which we have proposed for extracting the hand gestures features. The first algorithm is based on computing the region distance between the fingers and second one is about computing the shape descriptor of gesture boundary in radial fashion from the centroid of hand gestures. For matching the gesture the distance between two independent regions is computed for every row and column. Same process is repeated across the columns. The number of total region transitions are computed for every row and column. This number of transitions across rows and columns forms the feature vector. The proposed solution is easily able to deal with static and dynamic gestures. In case of second approach we compute the distance between the gesture centroid and shape boundaries at various angles from 0 to 360 degrees. These distances forms the feature vector. Comparison of result shows that this method is very effective in extracting the shape features and competent enough in terms of accuracy and speed. The gesture recognition algorithm mentioned in this paper can be used in automotive infotainment systems, consumer electronics where hardware needs to be cost effective and the response of the system should be fast enough.

Author(s) Details

Dr. Netra Lokhande
 School of Computer Engineering and Technology, MIT World Peace University, Kothrud, Pune, India

View Book :- http://bp.bookpi.org/index.php/bpi/catalog/book/170