This　paper　deals　with　sound　source　localization　and　number　estimation　in　indoor　environments　using　a　circular　microphone　array.　Multiple　sound　source　localization　is　achieved　by　performing　single　source　localization　at　each　selected　time-frequency　(TF)　point　of　received　signals　after　short-time　Fourier　transform.　A　TF　point　selection　method　is　proposed　to　reduce　the　computational　time,　which　depends　on　a　trained　SVM　with　power　and　power　ratio　of　TF　points　as　its　features.　Nonparametric　Bayesian　clustering　is　applied　on　the　obtained　DOA　estimates　to　identify　the　number　of　active　sources.　The　algorithm　is　shown　to　outperform　others　through　simulations.