In recent years, there has been an increase in video surveillance systems in public and private environments due to a heightened sense of security. The next generation of surveillance systems will be able to annotate video and locally coordinate the tracking of objects while multiplexing hundreds of video streams in real-time. In this paper, we present OmniEye, a wireless distributed real-time surveillance system composed of wireless smart cameras. OmniEye is comprised of custom-designed smart camera nodes called DSPcams that communicate using an IEEE 802.11 mesh network. These cameras provide wide-area coverage and local processing with the ability to direct a sparse number of high-resolution pan, tilt and zoom (PTZ) cameras that can home onto targets of interest. Each DSPcam performs local processing to help classify events and pro-actively draw an operator's attention when necessary. In video-streaming applications, maintaining high network utilization is required in order to maximize image quality as well as the number of cameras. Our experiments show that by using the standard 802.11 DCF MAC protocol for communication, the system does not scale beyond 5-6 cameras while each camera is streaming at 1 Mbps. Also, we see high levels of jitter in video transmissions. This performance degrades further for multi-hop scenarios due to the presence of hidden nodes. In order to improve the system's scalability and reliability, we propose a Time-Synchronized Application-level MAC protocol (TSAM) capable of operating on top of existing 802.11 protocols using commodity off-the-shelf hardware. Through analysis and experimental validation, we show how TSAM is able to improve throughput and provide bounded delay. Unlike traditional CSMA-based systems, TSAM gracefully degrades in a fair manner so that existing streams can still deliver data.