• Rohan U
• Rohan M
• Rahul G Prasad
• Madhu H N

Cricket, one of the most popular sports globally, generates an overwhelming amount of video content that poses challenges for efficient summarization. Automated cricket highlights generation offers a promising solution to reduce manual efforts while ensuring viewers receive concise, engaging match summaries. This survey explores state-of-the-art methods in cricket highlights generation, including video summarization, event detection using machine learning, and multimodal data integration. Existing approaches, while effective to some extent, face challenges such as handling noisy data, ensuring real-time processing, and incorporating contextual understanding of the game. Let’s see how advancements in deep learning, robust feature engineering, and computationally efficient pipelines can address these challenges and pave the way for more accurate and adaptive systems. This paper reviews existing methods, identifies gaps, and highlights opportunities for future research to guide the development of next-generation solutions in automated sports highlight generation.

Automated Sports Highlight Generation ,Cricket Video Summarization ,Event Detection in Sports ,Multimodal Data Integration ,Machine Learning in Sports Analytics ,Action Recognition in Cricket ,Audio-Visual Event Detection ,Deep Learning for Video Summarization ,Sports Video Processing ,Real-Time Highlight Generation

"AI-Based Cricket Match Highlights Generator", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 12, page no.c448-c452, December-2024, Available :http://www.jetir.org/papers/JETIR2412251.pdf

"AI-Based Cricket Match Highlights Generator", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 12, page no. ppc448-c452, December-2024, Available at : http://www.jetir.org/papers/JETIR2412251.pdf