Most of latest-generation multimedia systems are equipped with increasingly-effective object detection algorithms (e.g., intelligent video surveillance systems, augmented reality applications, sharing platforms for multimedia data, etc.). Unfortunately, image and video compression makes object detection more difficult since such operations erase most of the computed visual features. In this paper we propose a video rate control strategy that exploits a saliency metric to identify image regions where features are likely to be found. According to the pixel statistics, the approach decides whether to increase the coding quality or include some side information that specifies the keypoint locations. Experimental results on HEVC coder show that the proposed rate control algorithm improves both the detection accuracy and the rate-distortion performance with respect to state-of-the-art strategies.