Video Compression by Spatial and Temporal Dimension Reduction using Seam Carving Algorithm

There are several challenges associated with storing large videos such as high maintenance costs, increased complexity in securing large files, and the need for ample bandwidth for transmission. In such situations, videos are often compressed or converted into shorter clips. While it can offer a partial solution in specific cases, it usually comes at the cost of compromising video quality. This paper is designed to address the discussed issues. It reduces the video size by cropping and eliminating the pointless frames. It will reduce the dimensions and frames by identifying the continuous sections of pixels within the video that are less critical or less noticeable to the viewer while ensuring that the important content is well preserved. The process considers not only the video's spatial dimensions (width and height) but also the temporal dimension (time). The presented framework substantially reduces storage requirements, offering an alternative means to store videos that demand less maintenance and, consequently, fewer resource expenditures. It not only optimizes storage but also enhances accessibility and cost-effectiveness, making it a better solution for managing video archives in resource-intensive applications, such as long-term surveillance and video storage systems.